Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular
ilustraciones, graficas
- Autores:
-
Sanchez Rodriguez, Diego Alejandro
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/82216
- Palabra clave:
- 570 - Biología::573 - Sistemas fisiológicos específicos en animales, histología regional y fisiología en los animales
Cell aggregates
Morphogenesis model
Tissue engineering
Cell aggregates
Cell rearrangement
Self-learning KMC
Morphogenesis
Bioprinting simulation
Bioconvergence
Agregados celulares
Modelo de morfogenesis
Ingenieria de tejidos
Morfogenesis
Bioconvergencia
- Rights
- openAccess
- License
- Reconocimiento 4.0 Internacional
id |
UNACIONAL2_0643fd7c6438cd0fd880ed8e1f0f2064 |
---|---|
oai_identifier_str |
oai:repositorio.unal.edu.co:unal/82216 |
network_acronym_str |
UNACIONAL2 |
network_name_str |
Universidad Nacional de Colombia |
repository_id_str |
|
dc.title.eng.fl_str_mv |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular |
dc.title.translated.spa.fl_str_mv |
Simulation of the spatial structure and cellular organization evolution of cell aggregates arranged in various simple geometries, using a kinetic monte carlo method applied to a lattice model |
title |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular |
spellingShingle |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular 570 - Biología::573 - Sistemas fisiológicos específicos en animales, histología regional y fisiología en los animales Cell aggregates Morphogenesis model Tissue engineering Cell aggregates Cell rearrangement Self-learning KMC Morphogenesis Bioprinting simulation Bioconvergence Agregados celulares Modelo de morfogenesis Ingenieria de tejidos Morfogenesis Bioconvergencia |
title_short |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular |
title_full |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular |
title_fullStr |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular |
title_full_unstemmed |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular |
title_sort |
Simulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticular |
dc.creator.fl_str_mv |
Sanchez Rodriguez, Diego Alejandro |
dc.contributor.advisor.none.fl_str_mv |
Godoy Silva, Ruben Dario |
dc.contributor.author.none.fl_str_mv |
Sanchez Rodriguez, Diego Alejandro |
dc.contributor.editor.none.fl_str_mv |
Ramos Murillo Ana Isabel |
dc.contributor.researchgroup.spa.fl_str_mv |
Grupo de Investigación en Procesos Químicos y Bioquímicos |
dc.subject.ddc.spa.fl_str_mv |
570 - Biología::573 - Sistemas fisiológicos específicos en animales, histología regional y fisiología en los animales |
topic |
570 - Biología::573 - Sistemas fisiológicos específicos en animales, histología regional y fisiología en los animales Cell aggregates Morphogenesis model Tissue engineering Cell aggregates Cell rearrangement Self-learning KMC Morphogenesis Bioprinting simulation Bioconvergence Agregados celulares Modelo de morfogenesis Ingenieria de tejidos Morfogenesis Bioconvergencia |
dc.subject.proposal.eng.fl_str_mv |
Cell aggregates Morphogenesis model Tissue engineering Cell aggregates Cell rearrangement Self-learning KMC Morphogenesis Bioprinting simulation Bioconvergence |
dc.subject.proposal.spa.fl_str_mv |
Agregados celulares Modelo de morfogenesis Ingenieria de tejidos Morfogenesis Bioconvergencia |
description |
ilustraciones, graficas |
publishDate |
2021 |
dc.date.issued.none.fl_str_mv |
2021 |
dc.date.accessioned.none.fl_str_mv |
2022-08-31T16:12:48Z |
dc.date.available.none.fl_str_mv |
2022-08-31T16:12:48Z |
dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
dc.type.content.spa.fl_str_mv |
DataPaper Image Model Software Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
status_str |
acceptedVersion |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/82216 |
dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
url |
https://repositorio.unal.edu.co/handle/unal/82216 https://repositorio.unal.edu.co/ |
identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.indexed.spa.fl_str_mv |
RedCol LaReferencia |
dc.relation.references.spa.fl_str_mv |
Sánchez Rodríguez, D.A., A.I. Ramos-Murillo, and R.D. Godoy-Silva, Tissue engineering, 3DBioprinting, morphogenesis modelling and simulation of biostructures: Relevance, underpinning biological principles and future trends. Bioprinting, 2021. 24: p. e00171. Liu, N., et al., Advances in 3D bioprinting technology for cardiac tissue engineering and regeneration. Bioactive Materials, 2021. 6(5): p. 1388-1401. GODT. Global Observatory on Donation and Transplantation data. 2016 25 April 2020 [cited 2020; Available from: http://www.transplant-observatory.org/summary/. Health Resources and Services Administration. Organ Procurement and Transplantation Network. 26 April 2020 [cited 2020; Available from: https://optn.transplant.hrsa.gov/data/. Matai, I., et al., Progress in 3D bioprinting technology for tissue/organ regenerative engineering. Biomaterials, 2020. 226: p. 119536. Dzobo, K., K.S.C.M. Motaung, and A. Adesida, Recent Trends in Decellularized Extracellular Matrix Bioinks for 3D Printing: An Updated Review. International Journal of Molecular Sciences, 2019. 20(18): p. 4628. Gomes, M.E., et al., Tissue Engineering and Regenerative Medicine: New Trends and Directions—A Year in Review. Tissue Engineering Part B: Reviews, 2017. 23(3): p. 211-224. Lanza, R.P., R. Langer, and J. Vacanti, Chapter 1 - The History and Scope of Tissue Engineering. 2014. p. 3 - 8. Murphy, S.V. and A. Atala, 3D bioprinting of tissues and organs. Nature biotechnology, 2014. 32(8): p. 773-85. Neagu, A., Role of computer simulation to predict the outcome of 3D bioprinting. Journal of 3D Printing in Medicine, 2017. 1(2): p. 103-121. Brody, H., Regenerative medicine. Nature, 2016. 540: p. S49. Langer, R. and J. Vacanti, Tissue engineering. Science, 1993. 260(5110): p. 920-926. Ballet, F., Hepatotoxicity in drug development: detection, significance and solutions. Journal of Hepatology, 1997. 26: p. 26-36. Caponigro, G. and W.R. Sellers, Advances in the preclinical testing of cancer therapeutic hypotheses. Nature Reviews Drug Discovery, 2011. 10(3): p. 179-187. Schutgens, F. and H. Clevers, Human Organoids: Tools for Understanding Biology and Treating Diseases. Annu Rev Pathol, 2020. 15: p. 211-234. Clevers, H., Modeling Development and Disease with Organoids. Cell, 2016. 165(7): p. 1586- 1597. Dzobo, K., Taking a Full Snapshot of Cancer Biology: Deciphering the Tumor Microenvironment for Effective Cancer Therapy in the Oncology Clinic. OMICS: A Journal of Integrative Biology, 2020. 24(4): p. 175-179. Dzobo, K., et al., Three-Dimensional Organoids in Cancer Research: The Search for the Holy Grail of Preclinical Cancer Modeling. Omics, 2018. 22(12): p. 733-748. Kaushik, G., M.P. Ponnusamy, and S.K. Batra, Concise Review: Current Status of Three- Dimensional Organoids as Preclinical Models. STEM CELLS, 2018. 36(9): p. 1329-1340. Drost, J. and H. Clevers, Organoids in cancer research. Nature Reviews Cancer, 2018. 18(7): p. 407-418. Cellink. Bioconvergence is the future of healthcare. 2021; Available from: https://www.cellink.com/bioconvergence/. Authority, I.I. Bio-Convergence. The Future of Medicine. 2019; Available from: https://innovationisrael.org.il/en/reportchapter/bio-convergence. Senthebane, D.A., et al., The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer. International Journal of Molecular Sciences, 2017. 18(7). Bibliografía 217 Khademhosseini, A. and R. Langer, Microengineered hydrogels for tissue engineering. Biomaterials, 2007. 28(34): p. 5087-92. Kim, J.D., et al., Piezoelectric inkjet printing of polymers: Stem cell patterning on polymer substrates. Polymer, 2010. 51(10): p. 2147-2154. Mège, R.-M., Les molécules d'adhérence cellulaire: molécules morphogénétiques. médecine/sciences, 1991. 7: p. 544. Glazier, J.A. and F. Graner, Simulation of the differential adhesion driven rearrangement of biological cells. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 1993. 47(3): p. 2128-2154. Savill, N.J. and P. Hogeweg, Modelling Morphogenesis: From Single Cells to Crawling Slugs. Journal of Theoretical Biology, 1997. 184(3): p. 229 - 235. Walker, D.C., et al., Agent-based computational modeling of wounded epithelial cell monolayers. IEEE Transactions on NanoBioscience, 2004. 3(3): p. 153-163. Galle, J., et al., Individual cell-based models of tumor-environment interactions: Multiple effects of CD97 on tumor invasion. The American journal of pathology, 2006. 169(5): p. 1802-11. Takeichi, M., Cadherin cell adhesion receptors as a morphogenetic regulator. Science, 1991. 251(5000): p. 1451-5. Pepper, M., et al., Post-Bioprinting Processing Methods to Improve Cell Viability and Pattern Fidelity in Heterogeneous Tissue Test Systems. Vol. 2010. 2010. 259-62. Murphy, S.V., A. Skardal, and A. Atala, Evaluation of hydrogels for bio-printing applications. Journal of biomedical materials research. Part A, 2013. 101(1): p. 272-84. Jakab, K., et al., Tissue Engineering by Self-Assembly of Cells Printed into Topologically Defined Structures. Vol. 14. 2007. Jakab, K., et al., Tissue engineering by self-assembly and bio-printing of living cells. Biofabrication, 2010. 2(2): p. 022001-022001. Nogueira, J.A., et al., Simulation of a 3D Bioprinted Human Vascular Segment. Computer Aided Chemical Engineering, 2015: p. 684-688 Gjorevski, N., et al., Designer matrices for intestinal stem cell and organoid culture. Nature, 2016. 539(7630): p. 560-564. West, J.L. and J.A. Hubbell, Polymeric Biomaterials with Degradation Sites for Proteases Involved in Cell Migration. Macromolecules, 1999. 32(1): p. 241-244. Schiller, M., D. Javelaud, and A. Mauviel, TGF-beta-induced SMAD signaling and gene regulation: consequences for extracellular matrix remodeling and wound healing. Journal of dermatological science, 2004. 35(2): p. 83-92. Tamamura, Y., et al., Developmental regulation of Wnt/beta-catenin signals is required for growth plate assembly, cartilage integrity, and endochondral ossification. The Journal of biological chemistry, 2005. 280(19): p. 19185-95. Ingber, D.E., et al., Tissue engineering and developmental biology: going biomimetic. Tissue engineering, 2006. 12(12): p. 3265-83. Behonick, D.J. and Z. Werb, A bit of give and take: the relationship between the extracellular matrix and the developing chondrocyte. Mechanisms of development, 2003. 120(11): p. 1327-36. Hersel, U., C. Dahmen, and H. Kessler, RGD modified polymers: biomaterials for stimulated cell adhesion and beyond. Biomaterials, 2003. 24(24): p. 4385-415. 218 Título de la tesis o trabajo de investigación Price, R.L., K.M. Haberstroh, and T.J. Webster, Enhanced functions of osteoblasts on nanostructured surfaces of carbon and alumina. Medical and Biological Engineering and Computing, 2003. 41(3): p. 372-375. Teixeira, A.I., P.F. Nealey, and C.J. Murphy, Responses of human keratocytes to micro- and nanostructured substrates. Journal of biomedical materials research. Part A, 2004. 71(3): p. 369- 76. Discher, D.E., P. Janmey, and Y.L. Wang, Tissue cells feel and respond to the stiffness of their substrate. Science, 2005. 310(5751): p. 1139-43. Hopp, B., et al., Survival and proliferative ability of various living cell types after laser-induced forward transfer. Tissue engineering, 2005. 11(11-12): p. 1817-23. Stevens, M.M. and J.H. George, Exploring and engineering the cell surface interface. Science, 2005. 310(5751): p. 1135-8. Wu, Z., et al., Bioprinting three-dimensional cell-laden tissue constructs with controllable degradation. Scientific Reports, 2016. 6: p. 24474. Schon, B.S., G.J. Hooper, and T.B.F. Woodfield, Modular Tissue Assembly Strategies for Biofabrication of Engineered Cartilage. Annals of Biomedical Engineering, 2017. 45(1): p. 100- 114. Murphy, S.V. and A. Atala, 3D bioprinting of tissues and organs. Nat Biotechnol, 2014. 32(8): p. 773-85. Chang, R., J. Nam, and W. Sun, Direct cell writing of 3D microorgan for in vitro pharmacokinetic model. Tissue engineering. Part C, Methods, 2008. 14(2): p. 157-66. Nair, K., et al., Characterization of cell viability during bioprinting processes. Biotechnology journal, 2009. 4(8): p. 1168-77. Cui, X., et al., Thermal inkjet printing in tissue engineering and regenerative medicine. Recent patents on drug delivery & formulation, 2012. 6(2): p. 149-55. Robu, A., et al., Computer simulations of in vitro morphogenesis. Biosystems, 2012. 109(3): p. 430-43. Zhou, B., et al., Simulation of the gelation process of hydrogel droplets in 3D bioprinting. Vol. 16. 2016. 117-118. Fristrom, D., The cellular basis of epithelial morphogenesis. A review. Tissue and Cell, 1988. 20(5): p. 645 - 690. Radisic, M., et al., Functional assembly of engineered myocardium by electrical stimulation of cardiac myocytes cultured on scaffolds. Proceedings of the National Academy of Sciences of the United States of America, 2004. 101(52): p. 18129-34. Xu, T., et al., Viability and electrophysiology of neural cell structures generated by the inkjet printing method. Biomaterials, 2006. 27(19): p. 3580 - 3588. Steinberg, M.S., Adhesion in development: an historical overview. Developmental biology, 1996. 180(2): p. 377-88. Wang, Y., et al., Spheroid formation of hepatocarcinoma cells in microwells: Experiments and Monte Carlo simulations. PLoS ONE, 2016. 11(8). Mironov, V., et al., Organ printing: tissue spheroids as building blocks. Biomaterials, 2009. 30(12): p. 2164-74. Kelm, J.M., et al., A novel concept for scaffold-free vessel tissue engineering: self-assembly of microtissue building blocks. Journal of biotechnology, 2010. 148(1): p. 46-55. Tejavibulya, N., et al., Directed self-assembly of large scaffold-free multi-cellular honeycomb structures. Biofabrication, 2011. 3(3): p. 034110. Derby, B., Printing and prototyping of tissues and scaffolds. Science, 2012. 338(6109): p. 921-6. Bibliografía 219 Jakab, K., et al., Engineering biological structures of prescribed shape using self-assembling multicellular systems. Proceedings of the National Academy of Sciences of the United States of America, 2004. 101(9): p. 2864-2869. Jakab, K., et al., Relating cell and tissue mechanics: implications and applications. Developmental dynamics, 2008. 237(9): p. 2438-49. Steinberg, M.S., Reconstruction of Tissues by Dissociated Cells. Science, 1963. 141(3579): p. 401-408. Nakamura, M., et al., Biocompatible inkjet printing technique for designed seeding of individual living cells. Tissue engineering, 2005. 11(11-12): p. 1658-66. Freutel, M., et al., Finite element modeling of soft tissues: material models, tissue interaction and challenges. Clin Biomech (Bristol, Avon), 2014. 29(4): p. 363-72. Timpl, R., et al., Laminin--a glycoprotein from basement membranes. J Biol Chem, 1979. 254(19): p. 9933-7. Pankov, R. and K.M. Yamada, Fibronectin at a glance. J Cell Sci, 2002. 115(Pt 20): p. 3861-3. Vazin, T. and D.V. Schaffer, Engineering strategies to emulate the stem cell niche. Trends Biotechnol, 2010. 28(3): p. 117-24. Gleghorn, J.P., et al., Inhibitory morphogens and monopodial branching of the embryonic chicken lung. Developmental dynamics, 2012. 241(5): p. 852-62. Iber, D. and D. Menshykau, The control of branching morphogenesis. Open biology, 2013. 3(9): p. 130088-130088. Marga, F., et al., Developmental biology and tissue engineering. Birth Defects Research Part C: Embryo Today: Reviews, 2007. 81(4): p. 320-8. Betsch, M., et al., Incorporating 4D into Bioprinting: Real-Time Magnetically Directed Collagen Fiber Alignment for Generating Complex Multilayered Tissues. Advanced Healthcare Materials, 2018. 7(21): p. e1800894. Heinrich, M.A., et al., Bioprinting: 3D Bioprinting: from Benches to Translational Applications (Small 23/2019). Small, 2019. 15(23): p. 1970126. Hoshiba, T. and M. Tanaka, Decellularized matrices as in vitro models of extracellular matrix in tumor tissues at different malignant levels: Mechanism of 5-fluorouracil resistance in colorectal tumor cells. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 2016. 1863(11): p. 2749-2757. Kasza, K.E., et al., The cell as a material. Current opinion in cell biology, 2007. 19(1): p. 101-7. Mironov, V., V. Kasyanov, and R.R. Markwald, Organ printing: from bioprinter to organ biofabrication line. Current opinion in biotechnology, 2011. 22(5): p. 667-73. Marga, F., et al., Toward engineering functional organ modules by additive manufacturing. Biofabrication, 2012. 4(2): p. 022001. A., N., et al., Simulation of a 3D Bioprinted Human Vascular, in 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, J.K.H.a.R.G. Krist V. Gernaey, Editor. 2015, Elsevier B.V.: Copenhagen, Denmark. p. 684-688 Khoo, Z.X., et al., 3D printing of smart materials: A review on recent progresses in 4D printing. Virtual and Physical Prototyping, 2015. 10(3): p. 103-122. An, J., C.K. Chua, and V. Mironov, A Perspective on 4D Bioprinting. International Journal of Bioprinting, 2016. 220 Título de la tesis o trabajo de investigación Kamei, M., et al., Endothelial tubes assemble from intracellular vacuoles in vivo. Nature, 2006. 442(7101): p. 453-6. Alajati, A., et al., Spheroid-based engineering of a human vasculature in mice. Nature methods, 2008. 5(5): p. 439-45. Chang, R., J. Nam, and W. Sun, Effects of dispensing pressure and nozzle diameter on cell survival from solid freeform fabrication-based direct cell writing. Tissue engineering. Part A, 2008. 14(1): p. 41-8. Gunther, A., et al., A microfluidic platform for probing small artery structure and function. Lab on a chip, 2010. 10(18): p. 2341-9. Huh, D., et al., Reconstituting organ-level lung functions on a chip. Science, 2010. 328(5986): p. 1662-8. Xu, F., et al., A three-dimensional in vitro ovarian cancer coculture model using a highthroughput cell patterning platform. Biotechnology journal, 2011. 6(2): p. 204-212. Ghaemmaghami, A.M., et al., Biomimetic tissues on a chip for drug discovery. Drug discovery today, 2012. 17(3-4): p. 173-81. Knowlton, S., et al., Bioprinting for cancer research. Trends in biotechnology, 2015. 33(9): p. 504-13. Villasante, A. and G. Vunjak-Novakovic, Tissue-engineered models of human tumors for cancer research. Expert opinion on drug discovery, 2015. 10(3): p. 257-68. Lancaster, M.A., et al., Cerebral organoids model human brain development and microcephaly. Nature, 2013. 501(7467): p. 373-379. Wong, A.P., et al., Directed differentiation of human pluripotent stem cells into mature airway epithelia expressing functional CFTR protein. Nature Biotechnology, 2012. 30(9): p. 876-882. Clevers, H., STEM CELLS. What is an adult stem cell? Science, 2015. 350(6266): p. 1319-20. Eiraku, M. and Y. Sasai, Self-formation of layered neural structures in three-dimensional culture of ES cells. Current opinion in neurobiology, 2012. 22(5): p. 768-777. Lancaster, M.A. and J.A. Knoblich, Organogenesis in a dish: modeling development and disease using organoid technologies. Science, 2014. 345(6194): p. 1247125. Dekkers, J.F., et al., A functional CFTR assay using primary cystic fibrosis intestinal organoids. Nature Medicine, 2013. 19(7): p. 939-945. Ciancanelli, M.J., et al., Life-threatening influenza and impaired interferon amplification in human IRF7 deficiency. Science, 2015. 348(6233): p. 448. Firth, A.L., et al., Functional Gene Correction for Cystic Fibrosis in Lung Epithelial Cells Generated from Patient iPSCs. Cell Rep, 2015. 12(9): p. 1385-90. Benam, K.H., et al., Human Lung Small Airway-on-a-Chip Protocol, in 3D Cell Culture: Methods and Protocols, Z. Koledova, Editor. 2017, Springer New York: New York, NY. p. 345- 365. Bhatia, S.N. and D.E. Ingber, Microfluidic organs-on-chips. Nature Biotechnology, 2014. 32(8): p. 760-772. Kimura, H., Y. Sakai, and T. Fujii, Organ/body-on-a-chip based on microfluidic technology for drug discovery. Drug Metabolism and Pharmacokinetics, 2018. 33(1): p. 43-48. Domansky, K., et al., Perfused multiwell plate for 3D liver tissue engineering. Lab on a chip, 2010. 10(1): p. 51-8. Faulkner-Jones, A., et al., Bioprinting of human pluripotent stem cells and their directed differentiation into hepatocyte-like cells for the generation of mini-livers in 3D. Biofabrication, 2015. 7(4): p. 044102. Bibliografía 221 Ma, X., et al., Deterministically patterned biomimetic human iPSC-derived hepatic model via rapid 3D bioprinting. Proceedings of the National Academy of Sciences of the United States of America, 2016. 113(8): p. 2206-11. Dinh, N.-D., et al., Effective Light Directed Assembly of Building Blocks with Microscale Control. Small, 2017. 13. Kizawa, H., et al., Scaffold-free 3D bio-printed human liver tissue stably maintains metabolic functions useful for drug discovery. Biochemistry and Biophysics Reports, 2017. 10: p. 186-191. Stichler, S., et al., Double printing of hyaluronic acid/poly(glycidol) hybrid hydrogels with poly(ε-caprolactone) for MSC chondrogenesis. Biofabrication, 2017. 9(4). Kang, K., et al., Three-Dimensional Bioprinting of Hepatic Structures with Directly Converted Hepatocyte-Like Cells. Tissue engineering. Part A, 2018. 24(7-8): p. 576-583. Takebe, T., et al., Vascularized and functional human liver from an iPSC-derived organ bud transplant. Nature, 2013. 499(7459): p. 481-484. Bhise, N.S., et al., A liver-on-a-chip platform with bioprinted hepatic spheroids. Biofabrication, 2016. 8(1): p. 014101. Hirt, M.N., A. Hansen, and T. Eschenhagen, Cardiac Tissue Engineering. Circulation Research, 2014. 114(2): p. 354-367. Lind, J.U., et al., Instrumented cardiac microphysiological devices via multimaterial threedimensional printing. Nature Materials, 2017. 16(3): p. 303-308. Zhang, Y.S., et al., Bioprinting 3D microfibrous scaffolds for engineering endothelialized myocardium and heart-on-a-chip. Biomaterials, 2016. 110: p. 45-59. Ma, X., et al., 3D bioprinting of functional tissue models for personalized drug screening and in vitro disease modeling. Advanced drug delivery reviews, 2018. 132: p. 235-251. Jang, J., H.-G. Yi, and D.-W. Cho, 3D Printed Tissue Models: Present and Future. ACS Biomaterials Science & Engineering, 2016. 2(10): p. 1722-1731. Koch, L., et al., Skin tissue generation by laser cell printing. Biotechnology and bioengineering, 2012. 109(7): p. 1855-63. Lee, V., et al., Design and fabrication of human skin by three-dimensional bioprinting. Tissue engineering. Part C, Methods, 2014. 20(6): p. 473-84. Randall, M.J., et al., Advances in the Biofabrication of 3D Skin in vitro: Healthy and Pathological Models. Frontiers in Bioengineering and Biotechnology, 2018. 6(154). Lindberg, K., et al., In vitro propagation of human ocular surface epithelial cells for transplantation. Investigative Ophthalmology & Visual Science, 1993. 34(9): p. 2672-2679. Pellegrini, G., et al., Long-term restoration of damaged corneal surfaces with autologous cultivated corneal epithelium. The Lancet, 1997. 349(9057): p. 990-993. Rama, P., et al., Limbal stem-cell therapy and long-term corneal regeneration. New England journal of medicine, 2010. 363(2): p. 147-155. Lancaster, M.A. and J.A. Knoblich, Organogenesis in a dish: modeling development and disease using organoid technologies. Science, 2014. 345(6194). Longmire, T.A., et al., Efficient derivation of purified lung and thyroid progenitors from embryonic stem cells. Cell stem cell, 2012. 10(4): p. 398-411. Steinberg, M.S., Differential adhesion in morphogenesis: a modern view. Current Opinion in Genetics and Development 2007. 17(4): p. 281-6. Horning, J.L., et al., 3-D Tumor Model for In Vitro Evaluation of Anticancer Drugs. Molecular Pharmaceutics, 2008. 5(5): p. 849-862. 222 Título de la tesis o trabajo de investigación Flenner, E., et al., Kinetic Monte Carlo and Cellular Particle Dynamics Simulations of Multicellular Systems. Vol. 85. 2012. 031907. Shin, C.S., et al., 3D cancer tumor models for evaluating chemotherapeutic efficacy, in Biomaterials for Cancer Therapeutics, K. Park, Editor. 2013, Woodhead Publishing. p. 445-460. Hubert, C.G., et al., A Three-Dimensional Organoid Culture System Derived from Human Glioblastomas Recapitulates the Hypoxic Gradients and Cancer Stem Cell Heterogeneity of Tumors Found In Vivo. Cancer Res, 2016. 76(8): p. 2465-77. Fujii, M., et al., A Colorectal Tumor Organoid Library Demonstrates Progressive Loss of Niche Factor Requirements during Tumorigenesis. Cell Stem Cell, 2016. 18(6): p. 827-838. Liverani, C., et al., A biomimetic 3D model of hypoxia-driven cancer progression. Scientific Reports, 2019. 9(1): p. 12263. Tanner, K. and M.M. Gottesman, Beyond 3D culture models of cancer. Science Translational Medicine, 2015. 7(283): p. 283ps9-283ps9. Roberts, S., S. Peyman, and V. Speirs, Current and Emerging 3D Models to Study Breast Cancer, in Breast Cancer Metastasis and Drug Resistance. 2019. p. 413-427. Ringeisen, B.R., et al., Laser printing of pluripotent embryonal carcinoma cells. Tissue engineering, 2004. 10(3-4): p. 483-91. Matsusaki, M., et al., Three-dimensional human tissue chips fabricated by rapid and automatic inkjet cell printing. Advanced Healthcare Materials, 2013. 2(4): p. 534-9. Zhao, Y., et al., Three-dimensional printing of Hela cells for cervical tumor model in vitro. Biofabrication, 2014. 6(3): p. 035001. Yamada, K.M. and E. Cukierman, Modeling Tissue Morphogenesis and Cancer in 3D. Cell, 2007. 130(4): p. 601-610. Nantasanti, S., et al., Disease modeling and gene therapy of copper storage disease in canine hepatic organoids. Stem cell reports, 2015. 5(5): p. 895-907. Chaturvedi, R., et al., A Hybrid Discrete-Continuum Model for 3-D Skeletogenesis of the Vertebrate Limb, in International Conference on Cellular Automata. 2004. p. 543-552. Hespel, A.M., R. Wilhite, and J. Hudson, Invited review-applications for 3D printers in veterinary medicine. Veterinary Radiology & Ultrasound, 2014. 55(4): p. 347-358. Kamb, A., What's wrong with our cancer models? Nat Rev Drug Discov, 2005. 4(2): p. 161-5. Guillotin, B., et al., Laser assisted bioprinting of engineered tissue with high cell density and microscale organization. Biomaterials, 2010. 31(28): p. 7250-6. Campbell, P.G., et al., Engineered spatial patterns of FGF-2 immobilized on fibrin direct cell organization. Biomaterials, 2005. 26(33): p. 6762-70. Phillippi, J.A., et al., Microenvironments engineered by inkjet bioprinting spatially direct adult stem cells toward muscle- and bone-like subpopulations. Stem Cells, 2008. 26(1): p. 127-34. Norotte, C., et al., Scaffold-free vascular tissue engineering using bioprinting. Biomaterials, 2009. 30(30): p. 5910-7. Chrisey, D.B., Materials Processing: The Power of Direct Writing. Science, 2000. 289(5481): p. 879-81. Kattamis, N.T., et al., Thick film laser induced forward transfer for deposition of thermally and mechanically sensitive materials. Applied Physics Letters, 2007. 91(17): p. 171120. Koch, L., et al., Laser printing of skin cells and human stem cells. Tissue engineering. Part C, Methods, 2010. 16(5): p. 847-54. Gruene, M., et al., Laser printing of stem cells for biofabrication of scaffold-free autologous grafts. Tissue engineering. Part C, Methods, 2011. 17(1): p. 79-87. Duocastella, M., et al., Novel laser printing technique for miniaturized biosensors preparation. Sensors and Actuators B: Chemical, 2010. 145(1): p. 596-600. Bibliografía 223 Tekin, E., P.J. Smith, and U.S. Schubert, Inkjet printing as a deposition and patterning tool for polymers and inorganic particles. Soft Matter, 2008. 4(4): p. 703-713. Klebe, R.J., Cytoscribing: a method for micropositioning cells and the construction of two- and three-dimensional synthetic tissues. Experimental cell research, 1988. 179(2): p. 362-73. Okamoto, T., T. Suzuki, and N. Yamamoto, Microarray fabrication with covalent attachment of DNA using bubble jet technology. Nature biotechnology, 2000. 18(4): p. 438-41. Xu, T., et al., High-throughput production of single-cell microparticles using an inkjet printing technology. Journal of Manufacturing Science and Engineering, Transactions of the ASME, 2008. 130(2): p. 0210171-0210175. Cohen, D.L., et al., Direct freeform fabrication of seeded hydrogels in arbitrary geometries. Tissue engineering, 2006. 12(5): p. 1325-35. Visser, J., et al., Biofabrication of multi-material anatomically shaped tissue constructs. Biofabrication, 2013. 5(3): p. 035007. Khalil, S. and W. Sun, Biopolymer deposition for freeform fabrication of hydrogel tissue constructs. Materials Science & Engineering C, 2007. 27(3): p. 469-478. Guvendiren, M., H.D. Lu, and J.A. Burdick, Shear-thinning hydrogels for biomedical applications. Soft Matter, 2012. 8(2): p. 260-272. Hribar, K.C., et al., Light-assisted direct-write of 3D functional biomaterials. Lab on a Chip, 2014. 14(2): p. 268-275. Morris, V.B., et al., Mechanical Properties, Cytocompatibility and Manufacturability of Chitosan:PEGDA Hybrid-Gel Scaffolds by Stereolithography. Annals of Biomedical Engineering, 2017. 45(1): p. 286-296. Abdel Fattah, A.R., et al., In Situ 3D Label-Free Contactless Bioprinting of Cells through Diamagnetophoresis. ACS Biomaterials Science & Engineering, 2016. 2(12): p. 2133-2138. Tseng, H., et al., A three-dimensional co-culture model of the aortic valve using magnetic levitation. Acta Biomaterialia, 2014. 10(1): p. 173-182. Hennink, W.E. and C.F. van Nostrum, Novel crosslinking methods to design hydrogels. Advanced drug delivery reviews, 2002. 54(1): p. 13-36. Shin, S.R., et al., A Bioactive Carbon Nanotube-Based Ink for Printing 2D and 3D Flexible Electronics. Advanced Materials, 2016. 28(17): p. 3280-3289. Lind, J.U., et al., Instrumented cardiac microphysiological devices via multimaterial threedimensional printing. Nature Materials, 2017. 16(3): p. 303-308. Li, L., et al., In situ repair of bone and cartilage defects using 3D scanning and 3D printing. Scientific reports, 2017. 7(1): p. 9416. Hakimi, N., et al., Handheld skin printer: in situ formation of planar biomaterials and tissues. Lab on a chip, 2018. 18(10): p. 1440-1451. Silva, C., et al., Rational Design of a Triple-Layered Coaxial Extruder System: in silico and in vitro Evaluations Directed Toward Optimizing Cell Viability. International journal of bioprinting, 2020. 6(4): p. 282-282. Hufnagel, L., et al., On the mechanism of wing size determination in fly development. Proceedings of the National Academy of Sciences, 2007. 104(10): p. 3835-3840. Vincent, J.-P., A.G. Fletcher, and L.A. Baena-Lopez, Mechanisms and mechanics of cell competition in epithelia. Nature Reviews Molecular Cell Biology, 2013. 14(9): p. 581-591. Fletcher, A.G., F. Cooper, and R.E. Baker, Mechanocellular models of epithelial morphogenesis. Philosophical Transactions of the Royal Society B: Biological Sciences, 2017. 372(1720): p. 20150519. Kolesky, D.B., et al., 3D Bioprinting of Vascularized, Heterogeneous Cell-Laden Tissue Constructs. Advanced Materials, 2014. 26(19): p. 3124-3130. Kolesky, D.B., et al., Three-dimensional bioprinting of thick vascularized tissues. Proceedings of the National Academy of Sciences, 2016. 113(12): p. 3179-3184. Kang, H.-W., et al., A 3D bioprinting system to produce human-scale tissue constructs with structural integrity. Nature Biotechnology, 2016. 34(3): p. 312-319. Neagu, A., et al., Role of physical mechanisms in biological self-organization. Physical review letters, 2005. 95(17): p. 178104. Fleming, P.A., et al., Fusion of uniluminal vascular spheroids: a model for assembly of blood vessels. Developmental dynamics, 2010. 239(2): p. 398-406. Carter, S.B., Haptotaxis and the Mechanism of Cell Motility. Nature, 1967. 213(5073): p. 256- 260. Harris, A., Behavior of cultured cells on substrata of variable adhesiveness. Experimental cell research, 1973. 77(1): p. 285-97. Galle, J., M. Loeffler, and D. Drasdo, Modeling the effect of deregulated proliferation and apoptosis on the growth dynamics of epithelial cell populations in vitro. Biophysical journal, 2005. 88(1): p. 62-75. Merks, R.M.H., et al., Contact-Inhibited Chemotaxis in De Novo and Sprouting Blood-Vessel Growth. PLOS Computational Biology, 2008. 4(9): p. e1000163. Sengers, B.G., et al., Computational modelling of cell spreading and tissue regeneration in porous scaffolds. Biomaterials, 2007. 28(10): p. 1926-40. Hynes, R.O., Integrins: bidirectional, allosteric signaling machines. Cell, 2002. 110(6): p. 673- 87. Gumbiner, B.M., Cell adhesion: the molecular basis of tissue architecture and morphogenesis. Cell, 1996. 84(3): p. 345-57. Beysens, D.A., G. Forgacs, and J.A. Glazier, Cell sorting is analogous to phase ordering in fluids. Proceedings of the National Academy of Sciences of the United States of America, 2000. 97(17): p. 9467-9471. Foty, R.A. and M.S. Steinberg, The differential adhesion hypothesis: a direct evaluation. Developmental Biology, 2005. 278(1): p. 255-263. Steinberg, M.S., On the mechanism of tissue reconstruction by dissociated cells, III. Free energy relations and the organization of fused, heteronomic tissue fragments. Proceedings of the National Academy of Sciences of the United States of America, 1962. 48(10): p. 1769-76. Gierer, A., et al., Regeneration of hydra from reaggregated cells. Nature: New biology, 1972. 239(91): p. 98-101. Yamanaka, H., Y. Tanaka-Ohmura, and M. Dan-Sohkawa, What do dissociated embryonic cells of the starfish, Asterina pectinifera, do to reconstruct bipinnaria larvae? Journal of embryology and experimental morphology, 1986. 94: p. 61-71. Kipper, M.J., H.K. Kleinman, and F.W. Wang, New method for modeling connective-tissue cell migration: improved accuracy on motility parameters. Biophysical journal, 2007. 93(5): p. 1797- 808. Steinberg, M.S., Adhesion-guided multicellular assembly: a commentary upon the postulates, real and imagined, of the differential adhesion hypothesis, with special attention to computer simulations of cell sorting. Journal of Theoretical Biology, 1975. 55(2): p. 431 - 443. Foty, R.A., et al., Liquid properties of embryonic tissues: Measurement of interfacial tensions. Physical review letters, 1994. 72(14): p. 2298-2301. Foty, R.A., et al., Surface tensions of embryonic tissues predict their mutual envelopment behavior. Development, 1996. 122(5): p. 1611-20. Bibliografía 225 Marmottant, P., et al., The role of fluctuations and stress on the effective viscosity of cell aggregates. Proceedings of the National Academy of Sciences of the United States of America, 2009. 106(41): p. 17271-17275. Pajic-Lijakovic, I. and M. Milivojevic, Long-time viscoelasticity of multicellular surfaces caused by collective cell migration – Multi-scale modeling considerations. Seminars in Cell & Developmental Biology, 2019. 93: p. 87-96. Griffith, L.G. and G. Naughton, Tissue Engineering-Current Challenges and Expanding Opportunities. Science, 2002. 295(5557): p. 1009-1014. Norotte, C., et al., Experimental evaluation of apparent tissue surface tension based on the exact solution of the Laplace equation. Europhysics Letters, 2008. 81(46003). Mgharbel, A., H. Delanoe-Ayari, and J.P. Rieu, Measuring accurately liquid and tissue surface tension with a compression plate tensiometer. HFSP journal, 2009. 3(3): p. 213-21. Korff, T. and H.G. Augustin, Tensional forces in fibrillar extracellular matrices control directional capillary sprouting. Journal of cell science, 1999. 112 ( Pt 19): p. 3249-58. Friedl, P. and D. Gilmour, Collective cell migration in morphogenesis, regeneration and cancer. Nature reviews. Molecular cell biology 2009. 10(7): p. 445-57. Lo, C.M., et al., Cell movement is guided by the rigidity of the substrate. Biophysical journal, 2000. 79(1): p. 144-152. Mayor, R. and C. Carmona-Fontaine, Keeping in touch with contact inhibition of locomotion. Trends in cell biology, 2010. 20(6): p. 319-28. Goel, N.S. and G. Rogers, Computer simulation of engulfment and other movements of embryonic tissues. Journal of Theoretical Biology, 1978. 71(1): p. 103-140. Glazier, J.A., S.P. Gross, and J. Stavans, Dynamics of two-dimensional soap froths. Physical Review A, 1987. 36(1): p. 306-312. Stavans, J. and J.A. Glazier, Soap froth revisited: Dynamic scaling in the two-dimensional froth. Physical review letters, 1989. 62(11): p. 1318-1321. Turing, A.M., The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 1952. 237(641): p. 37-72. Wittwer, L.C., Roberto; Aland, Sebastian; Iber, Dagmar, Simulating Organogenesis in COMSOL: Phase-Field Based Simulations of Embryonic Lung Branching Morphogenesis. 2016. Wittwer, L.D., Phase-Field Based Simulations of Embryonic Branching Morphogenesis. 2017, ETH Zurich. Metzger, R.J., et al., The branching programme of mouse lung development. Nature, 2008. 453(7196): p. 745-50. Walker, D.C. and J. Southgate, The virtual cell--a candidate co-ordinator for 'middle-out' modelling of biological systems. Briefings in bioinformatics, 2009. 10(4): p. 450-61. Andasari, V., et al., Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion. PLOS ONE, 2012. 7(3): p. e33726. Ingber, D.E. and M. Levin, What lies at the interface of regenerative medicine and developmental biology? Development, 2007. 134(14): p. 2541-2547. Andreea Robu, L.S.-T., SIMMMC – An Informatic Application for Mmodelling and Simulating the Evolution of Multicellular Systems in the Vicinity of Biomaterials. Romaninan Journal of Biophysics, 2016. 26(3). Amar, J.G., The Monte Carlo Method in Science and Engineering. Computing in Science and Engineering, 2006. 8: p. 9-19. Fichthorn, K.A. and W.H. Weinberg, Theoretical foundations of dynamical Monte Carlo simulations. The Journal of Chemical Physics, 1991. 95(2): p. 1090-1096. Vineyard, G.H., Frequency factors and isotope effects in solid state rate processes. Journal of Physics and Chemistry of Solids, 1957. 3(1): p. 121-127. Sun, Y. and Q. Wang, Modeling and simulations of multicellular aggregate self-assembly in biofabrication using kinetic Monte Carlo methods. Soft Matter, 2013. 9(7): p. 2172-2186. Bortz, A.B., M.H. Kalos, and J.L. Lebowitz, A new algorithm for Monte Carlo simulation of Ising spin systems. Journal of Computational Physics, 1975. 17(1): p. 10-18. NEAGU, A., et al., COMPUTATIONAL MODELING OF TISSUE SELF-ASSEMBLY. Modern Physics Letters B, 2006. 20(20): p. 1217-1231. Schienbein, M., K. Franke, and H. Gruler, Random walk and directed movement: Comparison between inert particles and self-organized molecular machines. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 1994. 49(6): p. 5462-5471. Mombach, J.C. and J.A. Glazier, Single cell motion in aggregates of embryonic cells. Physical review letters, 1996. 76(16): p. 3032-3035. Graner, F. and J.A. Glazier, Simulation of biological cell sorting using a two-dimensional extended Potts model. Physical review letters, 1992. 69(13): p. 2013-2016. Glazier, J.A., A. Balter, and N.J. Poplawski, Magnetization to Morphogenesis: A Brief History of the Glazier-Graner Hogeweg Model, in Singl-Cell-Based Models in Biology and Medicine, M.A.J.C. A.R.A. Anderson, K.A. Rejniak, Editor. 2007, Mathematics and Biosciences in Interaction: Birkhäuser Verlag Basel / Switzerland. p. 79-106. Cickovski, T., et al., A Framework for Three-Dimensional Simulation of Morphogenesis. IEEE/ACM transactions on computational biology and bioinformatics, 2005. 2: p. 273-88. Merks, R.M.H. and P. Koolwijk, Modeling Morphogenesis in silico and in vitro: Towards Quantitative, Predictive, Cell-based Modeling. Mathematical Modelling of Natural Phenomena, 2009. 4(4): p. 149-171 Hester, S.D., et al., A multi-cell, multi-scale model of vertebrate segmentation and somite formation. PLoS computational biology, 2011. 7(10): p. e1002155. Rowlinson, J.S., Translation of J. D. van der Waals' “The thermodynamik theory of capillarity under the hypothesis of a continuous variation of density”. Journal of Statistical Physics, 1979. 20(2): p. 197-200. Yang, X., V. Mironov, and Q. Wang, Modeling fusion of cellular aggregates in biofabrication using phase field theories. Journal of theoretical biology, 2012. 303: p. 110-8. Yang, X., Y. Sun, and Q. Wang, A phase field approach for multicellular aggregate fusion in biofabrication. Journal of biomechanical engineering, 2013. 135(7): p. 71005. Flory, P.J., Principles of Polymer Chemistry. 1953, Ithaca, N.Y.: Cornell University Press. Doi, M., Introduction to Polymer Physics, ed. H. See. 1996: Clarendon Press Qin, R.S. and H.K. Bhadeshia, Phase field method. Materials Science and Technology, 2010. 26(7): p. 803-811. Aland, S., Modelling of two-phase flow with surface active particles, in Der Fakultät Mathematik und Naturwissenschaften. 2012, Technischen Universität Dresden. p. 127. Chen, L.-Q., Phase-Field Models for Microstructure Evolution. Annual Review of Materials Research, 2002. 32(1): p. 113-140. Folch, R., et al., Phase-field model for Hele-Shaw flows with arbitrary viscosity contrast. I. Theoretical approach. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 1999. 60(2 Pt B): p. 1724-33. Cahn, J.W. and J.E. Hilliard, Free Energy of a Nonuniform System. I. Interfacial Free Energy. The Journal of Chemical Physics, 1958. 28(2): p. 258-267. Bibliografía 227 Cahn, J.W. and J.E. Hilliard, Free Energy of a Nonuniform System. III. Nucleation in a Two‐ Component Incompressible Fluid. The Journal of Chemical Physics, 1959. 31(3): p. 688-699. Lervåg, K.Y. and J. Lowengrub, Analysis of the diffuse-domain method for solving PDEs in complex geometries. Communications in mathematical sciences, 2015. 13: p. 1473. Ibrahimi, O.A., et al., Analysis of mutations in fibroblast growth factor (FGF) and a pathogenic mutation in FGF receptor (FGFR) provides direct evidence for the symmetric two-end model for FGFR dimerization. Molecular and cellular biology, 2005. 25(2): p. 671-84. Francavilla, C., et al., Functional Proteomics Defines the Molecular Switch Underlying FGF Receptor Trafficking and Cellular Outputs. Molecular Cell, 2013. 51(6): p. 707-722. Donea, J., et al., Arbitrary Lagrangian–Eulerian Methods, in Encyclopedia of Computational Mechanics. 2004. Iber, D., et al., Simulating tissue morphogenesis and signaling. Methods in molecular biology, 2015. 1189: p. 323-38. Kockelkoren, J., H. Levine, and W.-J. Rappel, Computational approach for modeling intra- and extracellular dynamics. Physical Review E, 2003. 68(3): p. 037702. Kurics, T., D. Menshykau, and D. Iber, Feedback, receptor clustering, and receptor restriction to single cells yield large Turing spaces for ligand-receptor-based Turing models. Physical Review E, 2014. 90(2): p. 022716. Palsson, E. and H.G. Othmer, A model for individual and collective cell movement in Dictyostelium-discoideum. Proceedings of the National Academy of Sciences of the United States of America, 2000. 97(19): p. 10448-10453. Dallon, J.C. and H.G. Othmer, How cellular movement determines the collective force generated by the Dictyostelium discoideum slug. Journal of theoretical biology, 2004. 231(2): p. 203-22. Walker, D.C., et al., The epitheliome: agent-based modelling of the social behaviour of cells. Biosystems, 2004. 76(1-3): p. 89-100. Drasdo, D. and S. Hoehme, A single-cell-based model of tumor growth in vitro: Monolayers and spheroids. Physical biology, 2005. 2: p. 133-47. Chu, Y.S., et al., Johnson-Kendall-Roberts theory applied to living cells. Physical review letters, 2005. 94(2): p. 028102. Hoehme, S. and D. Drasdo, A cell-based simulation software for multi-cellular systems. Bioinformatics, 2010. 26(20): p. 2641-2. Hoehme, S., et al., Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proceedings of the National Academy of Sciences of the United States of America, 2010. 107(23): p. 10371-6. Hoffmann, M., et al., Spatial Organization of Mesenchymal Stem Cells In Vitro—Results from a New Individual Cell-Based Model with Podia. PLOS ONE, 2011. 6(7): p. e21960. Newman, T.J., Modeling Multicellular Systems Using Subcellular Elements. Mathematical Biosciences & Engineering, 2005. 2(3): p. 613-624. Zaman, M.H., et al., Computational model for cell migration in three-dimensional matrices. Biophysical journal, 2005. 89(2): p. 1389-97. Flenner, E., et al., Relating biophysical properties across scales, in Current Topics in Developmental Biology. 2008. p. 461-83. Sandersius, S.A. and T.J. Newman, Modeling cell rheology with the Subcellular Element Model. Physical biology, 2008. 5(1): p. 015002. Kosztin, I., G. Vunjak-Novakovic, and G. Forgacs, Colloquium: Modeling the dynamics of multicellular systems: Application to tissue engineering. Reviews of Modern Physics, 2012. 84(4): p. 1791-1805. 259. Chaikin, P.M., Principles of Condensed Matter Physics. 2000: Cambridge University Press. Alberts, B., et al., Molecular Biology of the Cell. 2002, New York: Garland Science. Pathmanathan, P., et al., A computational study of discrete mechanical tissue models. Physical Biology, 2009. 6(3): p. 036001. Phillips, J.C., et al., Scalable molecular dynamics with NAMD. Journal of computational chemistry, 2005. 26(16): p. 1781-802. Shafiee, A., et al., Post-deposition bioink self-assembly: a quantitative study. Biofabrication, 2015. 7(4): p. 045005. Cristea, A. and A. Neagu, Shape changes of bioprinted tissue constructs simulated by the Lattice Boltzmann method. Computers in biology and medicine, 2016. 70: p. 80-87. Silva, H.S. and M.L. Martins, A cellular automata model for cell differentiation. Physica A: Statistical Mechanics and its Applications, 2003. 322: p. 555-566. Garijo, N., et al., Stochastic cellular automata model of cell migration, proliferation and differentiation: Validation with in vitro cultures of muscle satellite cells. Journal of Theoretical Biology, 2012. 314: p. 1-9. Van Scoy, G.K., et al., A cellular automata model of bone formation. Mathematical Biosciences, 2017. 286: p. 58-64. Ben Youssef, B., Simulating Cell-Cell Interactions Using a Multicellular Three-Dimensional Computational Model of Tissue Growth. 2018. p. 215-228. Sipahi, R. and G.K.H. Zupanc, Stochastic cellular automata model of neurosphere growth: Roles of proliferative potential, contact inhibition, cell death, and phagocytosis. Journal of Theoretical Biology, 2018. 445: p. 151-165. Zupanc, G.K.H., F.B. Zupanc, and R. Sipahi, Stochastic cellular automata model of tumorous neurosphere growth: Roles of developmental maturity and cell death. Journal of Theoretical Biology, 2019. 467: p. 100-110. Beros, A., M. Chyba, and K. Noe, Co-evolving cellular automata for morphogenesis. Discrete & Continuous Dynamical Systems - B, 2019. 24(5): p. 2053-2071. Brodland, G.W. and J.H. Veldhuis, Assessing the mechanical energy costs of various tissue reshaping mechanisms. Biomech Model Mechanobiol, 2012. 11(8): p. 1137-47. Steinberg, M.S., Reconstruction of tissues by dissociated cells. Some morphogenetic tissue movements and the sorting out of embryonic cells may have a common explanation. Science, 1963. 141(3579): p. 401-8. Brodland, G.W. and H.H. Chen, The mechanics of heterotypic cell aggregates: insights from computer simulations. J Biomech Eng, 2000. 122(4): p. 402-7. Hwang, M., et al., Rule-Based Simulation of Multi-Cellular Biological Systems-A Review of Modeling Techniques. Cellular and molecular bioengineering, 2009. 2(3): p. 285-294. Rezende, R.A., et al., Organ Printing as an Information Technology. Procedia Engineering, 2015. 110: p. 151-158. Cohen, D.L., et al., Direct freeform fabrication of seeded hydrogels in arbitrary geometries. Tissue Eng, 2006. 12(5): p. 1325-35. Chang, R., J. Nam, and W. Sun, Direct cell writing of 3D microorgan for in vitro pharmacokinetic model. Tissue Eng Part C Methods, 2008. 14(2): p. 157-66. Hopp, B., et al., Survival and proliferative ability of various living cell types after laser-induced forward transfer. Tissue Eng, 2005. 11(11-12): p. 1817-23. Bibliografía 229 Mironov, V., V. Kasyanov, and R.R. Markwald, Organ printing: from bioprinter to organ biofabrication line. Curr Opin Biotechnol, 2011. 22(5): p. 667-73. Xu, F., et al., A three-dimensional in vitro ovarian cancer coculture model using a highthroughput cell patterning platform. Biotechnol J, 2011. 6(2): p. 204-212. Jiang, T., et al., Directing the Self-assembly of Tumour Spheroids by Bioprinting Cellular Heterogeneous Models within Alginate/Gelatin Hydrogels. Scientific Reports, 2017. 7(1): p. 4575. Lind, J.U., et al., Instrumented cardiac microphysiological devices via multimaterial threedimensional printing. 2017. 16(3): p. 303-308. Koti, P., et al., Use of GelMA for 3D printing of cardiac myocytes and fibroblasts. Journal of 3D printing in medicine, 2019. 3(1): p. 11-22. Klebe, R.J., Cytoscribing: a method for micropositioning cells and the construction of two- and three-dimensional synthetic tissues. Exp Cell Res, 1988. 179(2): p. 362-73. Nakamura, M., et al., Biocompatible inkjet printing technique for designed seeding of individual living cells. Tissue Eng, 2005. 11(11-12): p. 1658-66. Cui, X., et al., Thermal inkjet printing in tissue engineering and regenerative medicine. Recent Pat Drug Deliv Formul, 2012. 6(2): p. 149-55. Okamoto, T., T. Suzuki, and N. Yamamoto, Microarray fabrication with covalent attachment of DNA using bubble jet technology. Nat Biotechnol, 2000. 18(4): p. 438-41. Matsusaki, M., et al., Three-dimensional human tissue chips fabricated by rapid and automatic inkjet cell printing. Adv Healthc Mater, 2013. 2(4): p. 534-9. Lee, V., et al., Design and fabrication of human skin by three-dimensional bioprinting. Tissue Eng Part C Methods, 2014. 20(6): p. 473-84. Ringeisen, B.R., et al., Laser printing of pluripotent embryonal carcinoma cells. Tissue Eng, 2004. 10(3-4): p. 483-91. Gruene, M., et al., Laser printing of stem cells for biofabrication of scaffold-free autologous grafts. Tissue Eng Part C Methods, 2011. 17(1): p. 79-87. Guillemot, F., et al., High-throughput laser printing of cells and biomaterials for tissue engineering. Acta Biomaterialia, 2010. 6(7): p. 2494-2500. Ali, M., et al., Controlling laser-induced jet formation for bioprinting mesenchymal stem cells with high viability and high resolution. Biofabrication, 2014. 6(4): p. 045001. Stavans, J. and J.A. Glazier, Soap froth revisited: Dynamic scaling in the two-dimensional froth. Phys Rev Lett, 1989. 62(11): p. 1318-1321. Glazier, J.A. and F. Graner, Simulation of the differential adhesion driven rearrangement of biological cells. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, 1993. 47(3): p. 2128-2154. Amar, J.G., The Monte Carlo Method in Science and Engineering. Computing in Science and Engg., 2006. 8(2): p. 9–19. Steinberg, M.S., On the mechanism of tissue reconstruction by dissociated cells, III. Free energy relations and the organization of fused, heteronomic tissue fragments. Proc Natl Acad Sci U S A, 1962. 48(10): p. 1769-76. Steinberg, M.S., Differential adhesion in morphogenesis: a modern view. Curr Opin Genet Dev, 2007. 17(4): p. 281-6. Domansky, K., et al., Perfused multiwell plate for 3D liver tissue engineering. Lab Chip, 2010. 10(1): p. 51-8. 230 Título de la tesis o trabajo de investigación Cickovski, T.M., et al., A framework for three-dimensional simulation of morphogenesis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2005. 2(4): p. 273-288. Merks, R.M.H. and P. Koolwijk, Modeling Morphogenesis in silico and in vitro: Towards Quantitative, Predictive, Cell-based Modeling. Math. Model. Nat. Phenom., 2009. 4(4): p. 149- 171. R. Chaturvedi, C.H., J. A. Izaguirre, S. A. Newman, J. A. Glazier, M. Alber, A Hybrid Discrete- Continuum Model for 3-D Skeletogenesis of the Vertebrate Limb. International Conference on Cellular Automata, 2004: p. 543-552. Nicholas J.Savill, P., Modelling Morphogenesis: From Single Cells to Crawling Slugs. Journal of Theoretical Biology, 1997. 184(3): p. 229 - 235. Galle, J., et al., Individual cell-based models of tumor-environment interactions: Multiple effects of CD97 on tumor invasion. Am J Pathol, 2006. 169(5): p. 1802-11. Jakab, K., et al., Relating cell and tissue mechanics: implications and applications. Dev Dyn, 2008. 237(9): p. 2438-49. Jakab, K., et al., Organ printing: fiction or science. Biorheology, 2004. 41(3-4): p. 371-5. Yang, X., V. Mironov, and Q. Wang, Modeling fusion of cellular aggregates in biofabrication using phase field theories. J Theor Biol, 2012. 303: p. 110-8. Voter, A.F. INTRODUCTION TO THE KINETIC MONTE CARLO METHOD. 2007. Dordrecht: Springer Netherlands. Glazier James A, A.B.a.N.J.P., Magnetization to Morphogenesis: A Brief History of the Glazier- Graner Hogeweg Model, in Singl-Cell-Based Models in Biology and Medicine, M.A.J.C. A.R.A. Anderson, K.A. Rejniak, Editor. 2007, Mathematics and Biosciences in Interaction: Birkhäuser Verlag Basel / Switzerland. p. 79-106. Steinberg, M.S., Adhesion in development: an historical overview. Dev Biol, 1996. 180(2): p. 377-88. Chatterjee, A. and D.G. Vlachos, An overview of spatial microscopic and accelerated kinetic Monte Carlo methods. Journal of Computer-Aided Materials Design, 2007. 14(2): p. 253-308. Folch, R., et al., Phase-field model for Hele-Shaw flows with arbitrary viscosity contrast. I. Theoretical approach. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, 1999. 60(2 Pt B): p. 1724-33. Yang, X., Y. Sun, and Q. Wang, A phase field approach for multicellular aggregate fusion in biofabrication. J Biomech Eng, 2013. 135(7): p. 71005. Cristea, A. and A. Neagu, Shape changes of bioprinted tissue constructs simulated by the Lattice Boltzmann method. Comput Biol Med, 2016. 70: p. 80-87. Norris, J.R., Markov Chains. Cambridge Series in Statistical and Probabilistic Mathematics. 1997, Cambridge: Cambridge University Press. Feller, W., An Introduction to Probability Theory and Its Applications. Vol. 1. 1966. Blue, J.L., I. Beichl, and F. Sullivan, Faster Monte Carlo simulations. Physical Review E, 1995. 51(2): p. R867-R868. Rahman, T., et al., Atomistic studies of thin film growth. Optical Science and Technology, the SPIE 49th Annual Meeting. Vol. 5509. 2004: SPIE. Trushin, O., et al., Self-learning kinetic Monte Carlo method: Application to Cu(111). Physical Review B, 2005. 72(11): p. 115401. Foty, R.A., et al., Liquid properties of embryonic tissues: Measurement of interfacial tensions. Phys Rev Lett, 1994. 72(14): p. 2298-2301. Freutel, M., et al., Finite element modeling of soft tissues: Material models, tissue interaction and challenges. Clinical Biomechanics, 2014. 29(4): p. 363-372. Bibliografía 231 Marmottant, P., et al., The role of fluctuations and stress on the effective viscosity of cell aggregates. Proceedings of the National Academy of Sciences, 2009. 106(41): p. 17271-17275. Schienbein, M., K. Franke, and H. Gruler, Random walk and directed movement: Comparison between inert particles and self-organized molecular machines. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, 1994. 49(6): p. 5462-5471. Kipper, M.J., H.K. Kleinman, and F.W. Wang, New method for modeling connective-tissue cell migration: improved accuracy on motility parameters. Biophys J, 2007. 93(5): p. 1797-808. Mombach, J.C. and J.A. Glazier, Single cell motion in aggregates of embryonic cells. Phys Rev Lett, 1996. 76(16): p. 3032-3035. Flenner, E., et al., Relating biophysical properties across scales. Curr Top Dev Biol, 2008. 81: p. 461-83. Thomas, W.A. and J. Yancey, Can retinal adhesion mechanisms determine cell-sorting patterns: a test of the differential adhesion hypothesis. Development, 1988. 103(1): p. 37-48. Frenkel, J., Viscous flow of crystalline bodies under the action of surface tension. The Journal of Physics, USSR, 1945. 9: p. 385-391. J, D., Eshelby, Trans. AIME, 1949(185). Ma, X., et al., 3D bioprinting of functional tissue models for personalized drug screening and in vitro disease modeling. Adv Drug Deliv Rev, 2018. 132: p. 235-251. An, J., C.K. Chua, and V. Mironov, A Perspective on 4D Bioprinting. International Journal of Bioprinting; Vol 2, No 1 (2016), 2016. Nogueira JA., L.a., Marques TS., Oliveira DS., Mironov V., da Silva and R.R. JV., Simulation of a 3D Bioprinted Human Vascular Segment, in 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, J.K.H.a.R.G. Krist V. Gernaey, Editor. 2015, Elsevier B.V.: Copenhagen, Denmark. p. 684-688 Iber, D., et al., Simulating tissue morphogenesis and signaling. Methods Mol Biol, 2015. 1189: p. 323-38. Douglas Brown, R.H., and Wolfgang Christian, Tracker Video Analysis and Modeling Tool. October, 2020. Inc., T.M., Matlab. 2017. Han, Y., et al., Cultivation of recombinant Chinese hamster ovary cells grown as suspended aggregates in stirred vessels. J Biosci Bioeng, 2006. 102(5): p. 430-5. Pan, X., et al., Metabolic characterization of a CHO cell size increase phase in fed-batch cultures. Applied microbiology and biotechnology, 2017. 101(22): p. 8101-8113. |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Reconocimiento 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Reconocimiento 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.extent.spa.fl_str_mv |
227 páginas |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia |
dc.publisher.program.spa.fl_str_mv |
Bogotá - Ingeniería - Maestría en Ingeniería - Ingeniería Química |
dc.publisher.department.spa.fl_str_mv |
Departamento de Ingeniería Química y Ambiental |
dc.publisher.faculty.spa.fl_str_mv |
Facultad de Ingeniería |
dc.publisher.place.spa.fl_str_mv |
Bogotá, Colombia |
dc.publisher.branch.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Bogotá |
institution |
Universidad Nacional de Colombia |
bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/82216/1/license.txt https://repositorio.unal.edu.co/bitstream/unal/82216/3/1013662187.2022.pdf https://repositorio.unal.edu.co/bitstream/unal/82216/4/1013662187.2022.pdf.jpg |
bitstream.checksum.fl_str_mv |
8a4605be74aa9ea9d79846c1fba20a33 6c100c60a5389b2461a262ffe303ae0d f9c6eb0085f1523a48c09eb9da337d55 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
repository.mail.fl_str_mv |
repositorio_nal@unal.edu.co |
_version_ |
1814089321179774976 |
spelling |
Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Godoy Silva, Ruben Dario8866744983709005103dd37b112eec3aSanchez Rodriguez, Diego Alejandroe8edc325173e06bffcc7140bbcf1fa18600Ramos Murillo Ana IsabelGrupo de Investigación en Procesos Químicos y Bioquímicos2022-08-31T16:12:48Z2022-08-31T16:12:48Z2021https://repositorio.unal.edu.co/handle/unal/82216Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, graficasEsta tesis trata los modelos de morfogénesis, en particular los modelos de evolución guiada por contacto que son coherentes con la hipótesis de la adhesión diferencial. Se presenta una revisión de algunos modelos, sus principios biológicos subyacentes, la relevancia y aplicaciones en el marco de la bioimpresión, la ingeniería de tejidos y la bioconvergencia. Luego, se presentan los detalles de los modelos basados en métodos de Monte Carlo para profundizar más adelante en el modelo basados en algoritmos Kinetic Monte Carlo (KMC) , más específicamente, se describe en detalle un modelo KMC de autoaprendizaje (SL-KMC). Se presenta y explica la estructura algorítmica del código implementado, se evalúa el rendimiento del modelo y se compara con un modelo KMC tradicional. Finalmente, se realizan los procesos de calibración y validación, se observó que el modelo es capaz de replicar la evolución del sistema multicelular cuando las condiciones de energía interfacial del sistema simulado son similares a las del sistema de calibraciones. (Texto tomado de la fuente)This thesis treats the models for morphogenesis, in particular the contact-guided evolution models that are coherent with the differential adhesion hypothesis. A review of some models, their biological underpinning principles, the relevance and applications in the framework of bioprinting, tissue engineering and bioconvergence are presented. Then the details for the Monte Carlo methods-based models are presented to later deep dive into the Kinetic Monte Carlo (KMC) based model, and more specifically a Self-Learning KMC (SL-KMC) model is described to detail. The algorithmic structure of the implemented code is presented and explained, the model performance is assessed and compared with a traditional KMC model. Finally, the calibration and validation processes have been carried out, it was observed that the model is able to replicate the multicellular system evolution when the interfacial energy conditions of the simulated system are similar to those of the calibrations system.MaestríaMagíster en Ingeniería - Ingeniería Química227 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería QuímicaDepartamento de Ingeniería Química y AmbientalFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá570 - Biología::573 - Sistemas fisiológicos específicos en animales, histología regional y fisiología en los animalesCell aggregatesMorphogenesis modelTissue engineeringCell aggregatesCell rearrangementSelf-learning KMCMorphogenesisBioprinting simulationBioconvergenceAgregados celularesModelo de morfogenesisIngenieria de tejidosMorfogenesisBioconvergenciaSimulación de la evolución de la estructura espacial y organización celular de agregados celulares en diversas geometrías sencillas, mediante un método monte carlo cinético aplicado a un modelo reticularSimulation of the spatial structure and cellular organization evolution of cell aggregates arranged in various simple geometries, using a kinetic monte carlo method applied to a lattice modelTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionDataPaperImageModelSoftwareTexthttp://purl.org/redcol/resource_type/TMRedColLaReferenciaSánchez Rodríguez, D.A., A.I. Ramos-Murillo, and R.D. Godoy-Silva, Tissue engineering, 3DBioprinting, morphogenesis modelling and simulation of biostructures: Relevance, underpinning biological principles and future trends. Bioprinting, 2021. 24: p. e00171.Liu, N., et al., Advances in 3D bioprinting technology for cardiac tissue engineering and regeneration. Bioactive Materials, 2021. 6(5): p. 1388-1401.GODT. Global Observatory on Donation and Transplantation data. 2016 25 April 2020 [cited 2020; Available from: http://www.transplant-observatory.org/summary/.Health Resources and Services Administration. Organ Procurement and Transplantation Network. 26 April 2020 [cited 2020; Available from: https://optn.transplant.hrsa.gov/data/.Matai, I., et al., Progress in 3D bioprinting technology for tissue/organ regenerative engineering. Biomaterials, 2020. 226: p. 119536.Dzobo, K., K.S.C.M. Motaung, and A. Adesida, Recent Trends in Decellularized Extracellular Matrix Bioinks for 3D Printing: An Updated Review. International Journal of Molecular Sciences, 2019. 20(18): p. 4628.Gomes, M.E., et al., Tissue Engineering and Regenerative Medicine: New Trends and Directions—A Year in Review. Tissue Engineering Part B: Reviews, 2017. 23(3): p. 211-224.Lanza, R.P., R. Langer, and J. Vacanti, Chapter 1 - The History and Scope of Tissue Engineering. 2014. p. 3 - 8.Murphy, S.V. and A. Atala, 3D bioprinting of tissues and organs. Nature biotechnology, 2014. 32(8): p. 773-85.Neagu, A., Role of computer simulation to predict the outcome of 3D bioprinting. Journal of 3D Printing in Medicine, 2017. 1(2): p. 103-121.Brody, H., Regenerative medicine. Nature, 2016. 540: p. S49.Langer, R. and J. Vacanti, Tissue engineering. Science, 1993. 260(5110): p. 920-926.Ballet, F., Hepatotoxicity in drug development: detection, significance and solutions. Journal of Hepatology, 1997. 26: p. 26-36.Caponigro, G. and W.R. Sellers, Advances in the preclinical testing of cancer therapeutic hypotheses. Nature Reviews Drug Discovery, 2011. 10(3): p. 179-187.Schutgens, F. and H. Clevers, Human Organoids: Tools for Understanding Biology and Treating Diseases. Annu Rev Pathol, 2020. 15: p. 211-234.Clevers, H., Modeling Development and Disease with Organoids. Cell, 2016. 165(7): p. 1586- 1597.Dzobo, K., Taking a Full Snapshot of Cancer Biology: Deciphering the Tumor Microenvironment for Effective Cancer Therapy in the Oncology Clinic. OMICS: A Journal of Integrative Biology, 2020. 24(4): p. 175-179.Dzobo, K., et al., Three-Dimensional Organoids in Cancer Research: The Search for the Holy Grail of Preclinical Cancer Modeling. Omics, 2018. 22(12): p. 733-748.Kaushik, G., M.P. Ponnusamy, and S.K. Batra, Concise Review: Current Status of Three- Dimensional Organoids as Preclinical Models. STEM CELLS, 2018. 36(9): p. 1329-1340.Drost, J. and H. Clevers, Organoids in cancer research. Nature Reviews Cancer, 2018. 18(7): p. 407-418.Cellink. Bioconvergence is the future of healthcare. 2021; Available from: https://www.cellink.com/bioconvergence/.Authority, I.I. Bio-Convergence. The Future of Medicine. 2019; Available from: https://innovationisrael.org.il/en/reportchapter/bio-convergence.Senthebane, D.A., et al., The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer. International Journal of Molecular Sciences, 2017. 18(7). Bibliografía 217Khademhosseini, A. and R. Langer, Microengineered hydrogels for tissue engineering. Biomaterials, 2007. 28(34): p. 5087-92.Kim, J.D., et al., Piezoelectric inkjet printing of polymers: Stem cell patterning on polymer substrates. Polymer, 2010. 51(10): p. 2147-2154.Mège, R.-M., Les molécules d'adhérence cellulaire: molécules morphogénétiques. médecine/sciences, 1991. 7: p. 544.Glazier, J.A. and F. Graner, Simulation of the differential adhesion driven rearrangement of biological cells. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 1993. 47(3): p. 2128-2154.Savill, N.J. and P. Hogeweg, Modelling Morphogenesis: From Single Cells to Crawling Slugs. Journal of Theoretical Biology, 1997. 184(3): p. 229 - 235.Walker, D.C., et al., Agent-based computational modeling of wounded epithelial cell monolayers. IEEE Transactions on NanoBioscience, 2004. 3(3): p. 153-163.Galle, J., et al., Individual cell-based models of tumor-environment interactions: Multiple effects of CD97 on tumor invasion. The American journal of pathology, 2006. 169(5): p. 1802-11.Takeichi, M., Cadherin cell adhesion receptors as a morphogenetic regulator. Science, 1991. 251(5000): p. 1451-5.Pepper, M., et al., Post-Bioprinting Processing Methods to Improve Cell Viability and Pattern Fidelity in Heterogeneous Tissue Test Systems. Vol. 2010. 2010. 259-62.Murphy, S.V., A. Skardal, and A. Atala, Evaluation of hydrogels for bio-printing applications. Journal of biomedical materials research. Part A, 2013. 101(1): p. 272-84.Jakab, K., et al., Tissue Engineering by Self-Assembly of Cells Printed into Topologically Defined Structures. Vol. 14. 2007.Jakab, K., et al., Tissue engineering by self-assembly and bio-printing of living cells. Biofabrication, 2010. 2(2): p. 022001-022001.Nogueira, J.A., et al., Simulation of a 3D Bioprinted Human Vascular Segment. Computer Aided Chemical Engineering, 2015: p. 684-688Gjorevski, N., et al., Designer matrices for intestinal stem cell and organoid culture. Nature, 2016. 539(7630): p. 560-564.West, J.L. and J.A. Hubbell, Polymeric Biomaterials with Degradation Sites for Proteases Involved in Cell Migration. Macromolecules, 1999. 32(1): p. 241-244.Schiller, M., D. Javelaud, and A. Mauviel, TGF-beta-induced SMAD signaling and gene regulation: consequences for extracellular matrix remodeling and wound healing. Journal of dermatological science, 2004. 35(2): p. 83-92.Tamamura, Y., et al., Developmental regulation of Wnt/beta-catenin signals is required for growth plate assembly, cartilage integrity, and endochondral ossification. The Journal of biological chemistry, 2005. 280(19): p. 19185-95.Ingber, D.E., et al., Tissue engineering and developmental biology: going biomimetic. Tissue engineering, 2006. 12(12): p. 3265-83.Behonick, D.J. and Z. Werb, A bit of give and take: the relationship between the extracellular matrix and the developing chondrocyte. Mechanisms of development, 2003. 120(11): p. 1327-36.Hersel, U., C. Dahmen, and H. Kessler, RGD modified polymers: biomaterials for stimulated cell adhesion and beyond. Biomaterials, 2003. 24(24): p. 4385-415. 218 Título de la tesis o trabajo de investigaciónPrice, R.L., K.M. Haberstroh, and T.J. Webster, Enhanced functions of osteoblasts on nanostructured surfaces of carbon and alumina. Medical and Biological Engineering and Computing, 2003. 41(3): p. 372-375.Teixeira, A.I., P.F. Nealey, and C.J. Murphy, Responses of human keratocytes to micro- and nanostructured substrates. Journal of biomedical materials research. Part A, 2004. 71(3): p. 369- 76.Discher, D.E., P. Janmey, and Y.L. Wang, Tissue cells feel and respond to the stiffness of their substrate. Science, 2005. 310(5751): p. 1139-43.Hopp, B., et al., Survival and proliferative ability of various living cell types after laser-induced forward transfer. Tissue engineering, 2005. 11(11-12): p. 1817-23.Stevens, M.M. and J.H. George, Exploring and engineering the cell surface interface. Science, 2005. 310(5751): p. 1135-8.Wu, Z., et al., Bioprinting three-dimensional cell-laden tissue constructs with controllable degradation. Scientific Reports, 2016. 6: p. 24474.Schon, B.S., G.J. Hooper, and T.B.F. Woodfield, Modular Tissue Assembly Strategies for Biofabrication of Engineered Cartilage. Annals of Biomedical Engineering, 2017. 45(1): p. 100- 114.Murphy, S.V. and A. Atala, 3D bioprinting of tissues and organs. Nat Biotechnol, 2014. 32(8): p. 773-85.Chang, R., J. Nam, and W. Sun, Direct cell writing of 3D microorgan for in vitro pharmacokinetic model. Tissue engineering. Part C, Methods, 2008. 14(2): p. 157-66.Nair, K., et al., Characterization of cell viability during bioprinting processes. Biotechnology journal, 2009. 4(8): p. 1168-77.Cui, X., et al., Thermal inkjet printing in tissue engineering and regenerative medicine. Recent patents on drug delivery & formulation, 2012. 6(2): p. 149-55.Robu, A., et al., Computer simulations of in vitro morphogenesis. Biosystems, 2012. 109(3): p. 430-43.Zhou, B., et al., Simulation of the gelation process of hydrogel droplets in 3D bioprinting. Vol. 16. 2016. 117-118.Fristrom, D., The cellular basis of epithelial morphogenesis. A review. Tissue and Cell, 1988. 20(5): p. 645 - 690.Radisic, M., et al., Functional assembly of engineered myocardium by electrical stimulation of cardiac myocytes cultured on scaffolds. Proceedings of the National Academy of Sciences of the United States of America, 2004. 101(52): p. 18129-34.Xu, T., et al., Viability and electrophysiology of neural cell structures generated by the inkjet printing method. Biomaterials, 2006. 27(19): p. 3580 - 3588.Steinberg, M.S., Adhesion in development: an historical overview. Developmental biology, 1996. 180(2): p. 377-88.Wang, Y., et al., Spheroid formation of hepatocarcinoma cells in microwells: Experiments and Monte Carlo simulations. PLoS ONE, 2016. 11(8).Mironov, V., et al., Organ printing: tissue spheroids as building blocks. Biomaterials, 2009. 30(12): p. 2164-74.Kelm, J.M., et al., A novel concept for scaffold-free vessel tissue engineering: self-assembly of microtissue building blocks. Journal of biotechnology, 2010. 148(1): p. 46-55.Tejavibulya, N., et al., Directed self-assembly of large scaffold-free multi-cellular honeycomb structures. Biofabrication, 2011. 3(3): p. 034110.Derby, B., Printing and prototyping of tissues and scaffolds. Science, 2012. 338(6109): p. 921-6. Bibliografía 219Jakab, K., et al., Engineering biological structures of prescribed shape using self-assembling multicellular systems. Proceedings of the National Academy of Sciences of the United States of America, 2004. 101(9): p. 2864-2869.Jakab, K., et al., Relating cell and tissue mechanics: implications and applications. Developmental dynamics, 2008. 237(9): p. 2438-49.Steinberg, M.S., Reconstruction of Tissues by Dissociated Cells. Science, 1963. 141(3579): p. 401-408.Nakamura, M., et al., Biocompatible inkjet printing technique for designed seeding of individual living cells. Tissue engineering, 2005. 11(11-12): p. 1658-66.Freutel, M., et al., Finite element modeling of soft tissues: material models, tissue interaction and challenges. Clin Biomech (Bristol, Avon), 2014. 29(4): p. 363-72.Timpl, R., et al., Laminin--a glycoprotein from basement membranes. J Biol Chem, 1979. 254(19): p. 9933-7.Pankov, R. and K.M. Yamada, Fibronectin at a glance. J Cell Sci, 2002. 115(Pt 20): p. 3861-3.Vazin, T. and D.V. Schaffer, Engineering strategies to emulate the stem cell niche. Trends Biotechnol, 2010. 28(3): p. 117-24.Gleghorn, J.P., et al., Inhibitory morphogens and monopodial branching of the embryonic chicken lung. Developmental dynamics, 2012. 241(5): p. 852-62.Iber, D. and D. Menshykau, The control of branching morphogenesis. Open biology, 2013. 3(9): p. 130088-130088.Marga, F., et al., Developmental biology and tissue engineering. Birth Defects Research Part C: Embryo Today: Reviews, 2007. 81(4): p. 320-8.Betsch, M., et al., Incorporating 4D into Bioprinting: Real-Time Magnetically Directed Collagen Fiber Alignment for Generating Complex Multilayered Tissues. Advanced Healthcare Materials, 2018. 7(21): p. e1800894.Heinrich, M.A., et al., Bioprinting: 3D Bioprinting: from Benches to Translational Applications (Small 23/2019). Small, 2019. 15(23): p. 1970126.Hoshiba, T. and M. Tanaka, Decellularized matrices as in vitro models of extracellular matrix in tumor tissues at different malignant levels: Mechanism of 5-fluorouracil resistance in colorectal tumor cells. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 2016. 1863(11): p. 2749-2757.Kasza, K.E., et al., The cell as a material. Current opinion in cell biology, 2007. 19(1): p. 101-7.Mironov, V., V. Kasyanov, and R.R. Markwald, Organ printing: from bioprinter to organ biofabrication line. Current opinion in biotechnology, 2011. 22(5): p. 667-73.Marga, F., et al., Toward engineering functional organ modules by additive manufacturing. Biofabrication, 2012. 4(2): p. 022001.A., N., et al., Simulation of a 3D Bioprinted Human Vascular, in 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, J.K.H.a.R.G. Krist V. Gernaey, Editor. 2015, Elsevier B.V.: Copenhagen, Denmark. p. 684-688Khoo, Z.X., et al., 3D printing of smart materials: A review on recent progresses in 4D printing. Virtual and Physical Prototyping, 2015. 10(3): p. 103-122.An, J., C.K. Chua, and V. Mironov, A Perspective on 4D Bioprinting. International Journal of Bioprinting, 2016. 220 Título de la tesis o trabajo de investigaciónKamei, M., et al., Endothelial tubes assemble from intracellular vacuoles in vivo. Nature, 2006. 442(7101): p. 453-6.Alajati, A., et al., Spheroid-based engineering of a human vasculature in mice. Nature methods, 2008. 5(5): p. 439-45.Chang, R., J. Nam, and W. Sun, Effects of dispensing pressure and nozzle diameter on cell survival from solid freeform fabrication-based direct cell writing. Tissue engineering. Part A, 2008. 14(1): p. 41-8.Gunther, A., et al., A microfluidic platform for probing small artery structure and function. Lab on a chip, 2010. 10(18): p. 2341-9.Huh, D., et al., Reconstituting organ-level lung functions on a chip. Science, 2010. 328(5986): p. 1662-8.Xu, F., et al., A three-dimensional in vitro ovarian cancer coculture model using a highthroughput cell patterning platform. Biotechnology journal, 2011. 6(2): p. 204-212.Ghaemmaghami, A.M., et al., Biomimetic tissues on a chip for drug discovery. Drug discovery today, 2012. 17(3-4): p. 173-81.Knowlton, S., et al., Bioprinting for cancer research. Trends in biotechnology, 2015. 33(9): p. 504-13.Villasante, A. and G. Vunjak-Novakovic, Tissue-engineered models of human tumors for cancer research. Expert opinion on drug discovery, 2015. 10(3): p. 257-68.Lancaster, M.A., et al., Cerebral organoids model human brain development and microcephaly. Nature, 2013. 501(7467): p. 373-379.Wong, A.P., et al., Directed differentiation of human pluripotent stem cells into mature airway epithelia expressing functional CFTR protein. Nature Biotechnology, 2012. 30(9): p. 876-882.Clevers, H., STEM CELLS. What is an adult stem cell? Science, 2015. 350(6266): p. 1319-20.Eiraku, M. and Y. Sasai, Self-formation of layered neural structures in three-dimensional culture of ES cells. Current opinion in neurobiology, 2012. 22(5): p. 768-777.Lancaster, M.A. and J.A. Knoblich, Organogenesis in a dish: modeling development and disease using organoid technologies. Science, 2014. 345(6194): p. 1247125.Dekkers, J.F., et al., A functional CFTR assay using primary cystic fibrosis intestinal organoids. Nature Medicine, 2013. 19(7): p. 939-945.Ciancanelli, M.J., et al., Life-threatening influenza and impaired interferon amplification in human IRF7 deficiency. Science, 2015. 348(6233): p. 448.Firth, A.L., et al., Functional Gene Correction for Cystic Fibrosis in Lung Epithelial Cells Generated from Patient iPSCs. Cell Rep, 2015. 12(9): p. 1385-90.Benam, K.H., et al., Human Lung Small Airway-on-a-Chip Protocol, in 3D Cell Culture: Methods and Protocols, Z. Koledova, Editor. 2017, Springer New York: New York, NY. p. 345- 365.Bhatia, S.N. and D.E. Ingber, Microfluidic organs-on-chips. Nature Biotechnology, 2014. 32(8): p. 760-772.Kimura, H., Y. Sakai, and T. Fujii, Organ/body-on-a-chip based on microfluidic technology for drug discovery. Drug Metabolism and Pharmacokinetics, 2018. 33(1): p. 43-48.Domansky, K., et al., Perfused multiwell plate for 3D liver tissue engineering. Lab on a chip, 2010. 10(1): p. 51-8.Faulkner-Jones, A., et al., Bioprinting of human pluripotent stem cells and their directed differentiation into hepatocyte-like cells for the generation of mini-livers in 3D. Biofabrication, 2015. 7(4): p. 044102. Bibliografía 221Ma, X., et al., Deterministically patterned biomimetic human iPSC-derived hepatic model via rapid 3D bioprinting. Proceedings of the National Academy of Sciences of the United States of America, 2016. 113(8): p. 2206-11.Dinh, N.-D., et al., Effective Light Directed Assembly of Building Blocks with Microscale Control. Small, 2017. 13.Kizawa, H., et al., Scaffold-free 3D bio-printed human liver tissue stably maintains metabolic functions useful for drug discovery. Biochemistry and Biophysics Reports, 2017. 10: p. 186-191.Stichler, S., et al., Double printing of hyaluronic acid/poly(glycidol) hybrid hydrogels with poly(ε-caprolactone) for MSC chondrogenesis. Biofabrication, 2017. 9(4).Kang, K., et al., Three-Dimensional Bioprinting of Hepatic Structures with Directly Converted Hepatocyte-Like Cells. Tissue engineering. Part A, 2018. 24(7-8): p. 576-583.Takebe, T., et al., Vascularized and functional human liver from an iPSC-derived organ bud transplant. Nature, 2013. 499(7459): p. 481-484.Bhise, N.S., et al., A liver-on-a-chip platform with bioprinted hepatic spheroids. Biofabrication, 2016. 8(1): p. 014101.Hirt, M.N., A. Hansen, and T. Eschenhagen, Cardiac Tissue Engineering. Circulation Research, 2014. 114(2): p. 354-367.Lind, J.U., et al., Instrumented cardiac microphysiological devices via multimaterial threedimensional printing. Nature Materials, 2017. 16(3): p. 303-308.Zhang, Y.S., et al., Bioprinting 3D microfibrous scaffolds for engineering endothelialized myocardium and heart-on-a-chip. Biomaterials, 2016. 110: p. 45-59.Ma, X., et al., 3D bioprinting of functional tissue models for personalized drug screening and in vitro disease modeling. Advanced drug delivery reviews, 2018. 132: p. 235-251.Jang, J., H.-G. Yi, and D.-W. Cho, 3D Printed Tissue Models: Present and Future. ACS Biomaterials Science & Engineering, 2016. 2(10): p. 1722-1731.Koch, L., et al., Skin tissue generation by laser cell printing. Biotechnology and bioengineering, 2012. 109(7): p. 1855-63.Lee, V., et al., Design and fabrication of human skin by three-dimensional bioprinting. Tissue engineering. Part C, Methods, 2014. 20(6): p. 473-84.Randall, M.J., et al., Advances in the Biofabrication of 3D Skin in vitro: Healthy and Pathological Models. Frontiers in Bioengineering and Biotechnology, 2018. 6(154).Lindberg, K., et al., In vitro propagation of human ocular surface epithelial cells for transplantation. Investigative Ophthalmology & Visual Science, 1993. 34(9): p. 2672-2679.Pellegrini, G., et al., Long-term restoration of damaged corneal surfaces with autologous cultivated corneal epithelium. The Lancet, 1997. 349(9057): p. 990-993.Rama, P., et al., Limbal stem-cell therapy and long-term corneal regeneration. New England journal of medicine, 2010. 363(2): p. 147-155.Lancaster, M.A. and J.A. Knoblich, Organogenesis in a dish: modeling development and disease using organoid technologies. Science, 2014. 345(6194).Longmire, T.A., et al., Efficient derivation of purified lung and thyroid progenitors from embryonic stem cells. Cell stem cell, 2012. 10(4): p. 398-411.Steinberg, M.S., Differential adhesion in morphogenesis: a modern view. Current Opinion in Genetics and Development 2007. 17(4): p. 281-6.Horning, J.L., et al., 3-D Tumor Model for In Vitro Evaluation of Anticancer Drugs. Molecular Pharmaceutics, 2008. 5(5): p. 849-862. 222 Título de la tesis o trabajo de investigaciónFlenner, E., et al., Kinetic Monte Carlo and Cellular Particle Dynamics Simulations of Multicellular Systems. Vol. 85. 2012. 031907.Shin, C.S., et al., 3D cancer tumor models for evaluating chemotherapeutic efficacy, in Biomaterials for Cancer Therapeutics, K. Park, Editor. 2013, Woodhead Publishing. p. 445-460.Hubert, C.G., et al., A Three-Dimensional Organoid Culture System Derived from Human Glioblastomas Recapitulates the Hypoxic Gradients and Cancer Stem Cell Heterogeneity of Tumors Found In Vivo. Cancer Res, 2016. 76(8): p. 2465-77.Fujii, M., et al., A Colorectal Tumor Organoid Library Demonstrates Progressive Loss of Niche Factor Requirements during Tumorigenesis. Cell Stem Cell, 2016. 18(6): p. 827-838.Liverani, C., et al., A biomimetic 3D model of hypoxia-driven cancer progression. Scientific Reports, 2019. 9(1): p. 12263.Tanner, K. and M.M. Gottesman, Beyond 3D culture models of cancer. Science Translational Medicine, 2015. 7(283): p. 283ps9-283ps9.Roberts, S., S. Peyman, and V. Speirs, Current and Emerging 3D Models to Study Breast Cancer, in Breast Cancer Metastasis and Drug Resistance. 2019. p. 413-427.Ringeisen, B.R., et al., Laser printing of pluripotent embryonal carcinoma cells. Tissue engineering, 2004. 10(3-4): p. 483-91.Matsusaki, M., et al., Three-dimensional human tissue chips fabricated by rapid and automatic inkjet cell printing. Advanced Healthcare Materials, 2013. 2(4): p. 534-9.Zhao, Y., et al., Three-dimensional printing of Hela cells for cervical tumor model in vitro. Biofabrication, 2014. 6(3): p. 035001.Yamada, K.M. and E. Cukierman, Modeling Tissue Morphogenesis and Cancer in 3D. Cell, 2007. 130(4): p. 601-610.Nantasanti, S., et al., Disease modeling and gene therapy of copper storage disease in canine hepatic organoids. Stem cell reports, 2015. 5(5): p. 895-907.Chaturvedi, R., et al., A Hybrid Discrete-Continuum Model for 3-D Skeletogenesis of the Vertebrate Limb, in International Conference on Cellular Automata. 2004. p. 543-552.Hespel, A.M., R. Wilhite, and J. Hudson, Invited review-applications for 3D printers in veterinary medicine. Veterinary Radiology & Ultrasound, 2014. 55(4): p. 347-358.Kamb, A., What's wrong with our cancer models? Nat Rev Drug Discov, 2005. 4(2): p. 161-5.Guillotin, B., et al., Laser assisted bioprinting of engineered tissue with high cell density and microscale organization. Biomaterials, 2010. 31(28): p. 7250-6.Campbell, P.G., et al., Engineered spatial patterns of FGF-2 immobilized on fibrin direct cell organization. Biomaterials, 2005. 26(33): p. 6762-70.Phillippi, J.A., et al., Microenvironments engineered by inkjet bioprinting spatially direct adult stem cells toward muscle- and bone-like subpopulations. Stem Cells, 2008. 26(1): p. 127-34.Norotte, C., et al., Scaffold-free vascular tissue engineering using bioprinting. Biomaterials, 2009. 30(30): p. 5910-7.Chrisey, D.B., Materials Processing: The Power of Direct Writing. Science, 2000. 289(5481): p. 879-81.Kattamis, N.T., et al., Thick film laser induced forward transfer for deposition of thermally and mechanically sensitive materials. Applied Physics Letters, 2007. 91(17): p. 171120.Koch, L., et al., Laser printing of skin cells and human stem cells. Tissue engineering. Part C, Methods, 2010. 16(5): p. 847-54.Gruene, M., et al., Laser printing of stem cells for biofabrication of scaffold-free autologous grafts. Tissue engineering. Part C, Methods, 2011. 17(1): p. 79-87.Duocastella, M., et al., Novel laser printing technique for miniaturized biosensors preparation. Sensors and Actuators B: Chemical, 2010. 145(1): p. 596-600. Bibliografía 223Tekin, E., P.J. Smith, and U.S. Schubert, Inkjet printing as a deposition and patterning tool for polymers and inorganic particles. Soft Matter, 2008. 4(4): p. 703-713.Klebe, R.J., Cytoscribing: a method for micropositioning cells and the construction of two- and three-dimensional synthetic tissues. Experimental cell research, 1988. 179(2): p. 362-73.Okamoto, T., T. Suzuki, and N. Yamamoto, Microarray fabrication with covalent attachment of DNA using bubble jet technology. Nature biotechnology, 2000. 18(4): p. 438-41.Xu, T., et al., High-throughput production of single-cell microparticles using an inkjet printing technology. Journal of Manufacturing Science and Engineering, Transactions of the ASME, 2008. 130(2): p. 0210171-0210175.Cohen, D.L., et al., Direct freeform fabrication of seeded hydrogels in arbitrary geometries. Tissue engineering, 2006. 12(5): p. 1325-35.Visser, J., et al., Biofabrication of multi-material anatomically shaped tissue constructs. Biofabrication, 2013. 5(3): p. 035007.Khalil, S. and W. Sun, Biopolymer deposition for freeform fabrication of hydrogel tissue constructs. Materials Science & Engineering C, 2007. 27(3): p. 469-478.Guvendiren, M., H.D. Lu, and J.A. Burdick, Shear-thinning hydrogels for biomedical applications. Soft Matter, 2012. 8(2): p. 260-272.Hribar, K.C., et al., Light-assisted direct-write of 3D functional biomaterials. Lab on a Chip, 2014. 14(2): p. 268-275.Morris, V.B., et al., Mechanical Properties, Cytocompatibility and Manufacturability of Chitosan:PEGDA Hybrid-Gel Scaffolds by Stereolithography. Annals of Biomedical Engineering, 2017. 45(1): p. 286-296.Abdel Fattah, A.R., et al., In Situ 3D Label-Free Contactless Bioprinting of Cells through Diamagnetophoresis. ACS Biomaterials Science & Engineering, 2016. 2(12): p. 2133-2138.Tseng, H., et al., A three-dimensional co-culture model of the aortic valve using magnetic levitation. Acta Biomaterialia, 2014. 10(1): p. 173-182.Hennink, W.E. and C.F. van Nostrum, Novel crosslinking methods to design hydrogels. Advanced drug delivery reviews, 2002. 54(1): p. 13-36.Shin, S.R., et al., A Bioactive Carbon Nanotube-Based Ink for Printing 2D and 3D Flexible Electronics. Advanced Materials, 2016. 28(17): p. 3280-3289.Lind, J.U., et al., Instrumented cardiac microphysiological devices via multimaterial threedimensional printing. Nature Materials, 2017. 16(3): p. 303-308.Li, L., et al., In situ repair of bone and cartilage defects using 3D scanning and 3D printing. Scientific reports, 2017. 7(1): p. 9416.Hakimi, N., et al., Handheld skin printer: in situ formation of planar biomaterials and tissues. Lab on a chip, 2018. 18(10): p. 1440-1451.Silva, C., et al., Rational Design of a Triple-Layered Coaxial Extruder System: in silico and in vitro Evaluations Directed Toward Optimizing Cell Viability. International journal of bioprinting, 2020. 6(4): p. 282-282.Hufnagel, L., et al., On the mechanism of wing size determination in fly development. Proceedings of the National Academy of Sciences, 2007. 104(10): p. 3835-3840.Vincent, J.-P., A.G. Fletcher, and L.A. Baena-Lopez, Mechanisms and mechanics of cell competition in epithelia. Nature Reviews Molecular Cell Biology, 2013. 14(9): p. 581-591.Fletcher, A.G., F. Cooper, and R.E. Baker, Mechanocellular models of epithelial morphogenesis. Philosophical Transactions of the Royal Society B: Biological Sciences, 2017. 372(1720): p. 20150519.Kolesky, D.B., et al., 3D Bioprinting of Vascularized, Heterogeneous Cell-Laden Tissue Constructs. Advanced Materials, 2014. 26(19): p. 3124-3130.Kolesky, D.B., et al., Three-dimensional bioprinting of thick vascularized tissues. Proceedings of the National Academy of Sciences, 2016. 113(12): p. 3179-3184.Kang, H.-W., et al., A 3D bioprinting system to produce human-scale tissue constructs with structural integrity. Nature Biotechnology, 2016. 34(3): p. 312-319.Neagu, A., et al., Role of physical mechanisms in biological self-organization. Physical review letters, 2005. 95(17): p. 178104.Fleming, P.A., et al., Fusion of uniluminal vascular spheroids: a model for assembly of blood vessels. Developmental dynamics, 2010. 239(2): p. 398-406.Carter, S.B., Haptotaxis and the Mechanism of Cell Motility. Nature, 1967. 213(5073): p. 256- 260.Harris, A., Behavior of cultured cells on substrata of variable adhesiveness. Experimental cell research, 1973. 77(1): p. 285-97.Galle, J., M. Loeffler, and D. Drasdo, Modeling the effect of deregulated proliferation and apoptosis on the growth dynamics of epithelial cell populations in vitro. Biophysical journal, 2005. 88(1): p. 62-75.Merks, R.M.H., et al., Contact-Inhibited Chemotaxis in De Novo and Sprouting Blood-Vessel Growth. PLOS Computational Biology, 2008. 4(9): p. e1000163.Sengers, B.G., et al., Computational modelling of cell spreading and tissue regeneration in porous scaffolds. Biomaterials, 2007. 28(10): p. 1926-40.Hynes, R.O., Integrins: bidirectional, allosteric signaling machines. Cell, 2002. 110(6): p. 673- 87.Gumbiner, B.M., Cell adhesion: the molecular basis of tissue architecture and morphogenesis. Cell, 1996. 84(3): p. 345-57.Beysens, D.A., G. Forgacs, and J.A. Glazier, Cell sorting is analogous to phase ordering in fluids. Proceedings of the National Academy of Sciences of the United States of America, 2000. 97(17): p. 9467-9471.Foty, R.A. and M.S. Steinberg, The differential adhesion hypothesis: a direct evaluation. Developmental Biology, 2005. 278(1): p. 255-263.Steinberg, M.S., On the mechanism of tissue reconstruction by dissociated cells, III. Free energy relations and the organization of fused, heteronomic tissue fragments. Proceedings of the National Academy of Sciences of the United States of America, 1962. 48(10): p. 1769-76.Gierer, A., et al., Regeneration of hydra from reaggregated cells. Nature: New biology, 1972. 239(91): p. 98-101.Yamanaka, H., Y. Tanaka-Ohmura, and M. Dan-Sohkawa, What do dissociated embryonic cells of the starfish, Asterina pectinifera, do to reconstruct bipinnaria larvae? Journal of embryology and experimental morphology, 1986. 94: p. 61-71.Kipper, M.J., H.K. Kleinman, and F.W. Wang, New method for modeling connective-tissue cell migration: improved accuracy on motility parameters. Biophysical journal, 2007. 93(5): p. 1797- 808.Steinberg, M.S., Adhesion-guided multicellular assembly: a commentary upon the postulates, real and imagined, of the differential adhesion hypothesis, with special attention to computer simulations of cell sorting. Journal of Theoretical Biology, 1975. 55(2): p. 431 - 443.Foty, R.A., et al., Liquid properties of embryonic tissues: Measurement of interfacial tensions. Physical review letters, 1994. 72(14): p. 2298-2301.Foty, R.A., et al., Surface tensions of embryonic tissues predict their mutual envelopment behavior. Development, 1996. 122(5): p. 1611-20. Bibliografía 225Marmottant, P., et al., The role of fluctuations and stress on the effective viscosity of cell aggregates. Proceedings of the National Academy of Sciences of the United States of America, 2009. 106(41): p. 17271-17275.Pajic-Lijakovic, I. and M. Milivojevic, Long-time viscoelasticity of multicellular surfaces caused by collective cell migration – Multi-scale modeling considerations. Seminars in Cell & Developmental Biology, 2019. 93: p. 87-96.Griffith, L.G. and G. Naughton, Tissue Engineering-Current Challenges and Expanding Opportunities. Science, 2002. 295(5557): p. 1009-1014.Norotte, C., et al., Experimental evaluation of apparent tissue surface tension based on the exact solution of the Laplace equation. Europhysics Letters, 2008. 81(46003).Mgharbel, A., H. Delanoe-Ayari, and J.P. Rieu, Measuring accurately liquid and tissue surface tension with a compression plate tensiometer. HFSP journal, 2009. 3(3): p. 213-21.Korff, T. and H.G. Augustin, Tensional forces in fibrillar extracellular matrices control directional capillary sprouting. Journal of cell science, 1999. 112 ( Pt 19): p. 3249-58.Friedl, P. and D. Gilmour, Collective cell migration in morphogenesis, regeneration and cancer. Nature reviews. Molecular cell biology 2009. 10(7): p. 445-57.Lo, C.M., et al., Cell movement is guided by the rigidity of the substrate. Biophysical journal, 2000. 79(1): p. 144-152.Mayor, R. and C. Carmona-Fontaine, Keeping in touch with contact inhibition of locomotion. Trends in cell biology, 2010. 20(6): p. 319-28.Goel, N.S. and G. Rogers, Computer simulation of engulfment and other movements of embryonic tissues. Journal of Theoretical Biology, 1978. 71(1): p. 103-140.Glazier, J.A., S.P. Gross, and J. Stavans, Dynamics of two-dimensional soap froths. Physical Review A, 1987. 36(1): p. 306-312.Stavans, J. and J.A. Glazier, Soap froth revisited: Dynamic scaling in the two-dimensional froth. Physical review letters, 1989. 62(11): p. 1318-1321.Turing, A.M., The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 1952. 237(641): p. 37-72.Wittwer, L.C., Roberto; Aland, Sebastian; Iber, Dagmar, Simulating Organogenesis in COMSOL: Phase-Field Based Simulations of Embryonic Lung Branching Morphogenesis. 2016.Wittwer, L.D., Phase-Field Based Simulations of Embryonic Branching Morphogenesis. 2017, ETH Zurich.Metzger, R.J., et al., The branching programme of mouse lung development. Nature, 2008. 453(7196): p. 745-50.Walker, D.C. and J. Southgate, The virtual cell--a candidate co-ordinator for 'middle-out' modelling of biological systems. Briefings in bioinformatics, 2009. 10(4): p. 450-61.Andasari, V., et al., Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion. PLOS ONE, 2012. 7(3): p. e33726.Ingber, D.E. and M. Levin, What lies at the interface of regenerative medicine and developmental biology? Development, 2007. 134(14): p. 2541-2547.Andreea Robu, L.S.-T., SIMMMC – An Informatic Application for Mmodelling and Simulating the Evolution of Multicellular Systems in the Vicinity of Biomaterials. Romaninan Journal of Biophysics, 2016. 26(3).Amar, J.G., The Monte Carlo Method in Science and Engineering. Computing in Science and Engineering, 2006. 8: p. 9-19.Fichthorn, K.A. and W.H. Weinberg, Theoretical foundations of dynamical Monte Carlo simulations. The Journal of Chemical Physics, 1991. 95(2): p. 1090-1096.Vineyard, G.H., Frequency factors and isotope effects in solid state rate processes. Journal of Physics and Chemistry of Solids, 1957. 3(1): p. 121-127.Sun, Y. and Q. Wang, Modeling and simulations of multicellular aggregate self-assembly in biofabrication using kinetic Monte Carlo methods. Soft Matter, 2013. 9(7): p. 2172-2186.Bortz, A.B., M.H. Kalos, and J.L. Lebowitz, A new algorithm for Monte Carlo simulation of Ising spin systems. Journal of Computational Physics, 1975. 17(1): p. 10-18.NEAGU, A., et al., COMPUTATIONAL MODELING OF TISSUE SELF-ASSEMBLY. Modern Physics Letters B, 2006. 20(20): p. 1217-1231.Schienbein, M., K. Franke, and H. Gruler, Random walk and directed movement: Comparison between inert particles and self-organized molecular machines. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 1994. 49(6): p. 5462-5471.Mombach, J.C. and J.A. Glazier, Single cell motion in aggregates of embryonic cells. Physical review letters, 1996. 76(16): p. 3032-3035.Graner, F. and J.A. Glazier, Simulation of biological cell sorting using a two-dimensional extended Potts model. Physical review letters, 1992. 69(13): p. 2013-2016.Glazier, J.A., A. Balter, and N.J. Poplawski, Magnetization to Morphogenesis: A Brief History of the Glazier-Graner Hogeweg Model, in Singl-Cell-Based Models in Biology and Medicine, M.A.J.C. A.R.A. Anderson, K.A. Rejniak, Editor. 2007, Mathematics and Biosciences in Interaction: Birkhäuser Verlag Basel / Switzerland. p. 79-106.Cickovski, T., et al., A Framework for Three-Dimensional Simulation of Morphogenesis. IEEE/ACM transactions on computational biology and bioinformatics, 2005. 2: p. 273-88.Merks, R.M.H. and P. Koolwijk, Modeling Morphogenesis in silico and in vitro: Towards Quantitative, Predictive, Cell-based Modeling. Mathematical Modelling of Natural Phenomena, 2009. 4(4): p. 149-171Hester, S.D., et al., A multi-cell, multi-scale model of vertebrate segmentation and somite formation. PLoS computational biology, 2011. 7(10): p. e1002155.Rowlinson, J.S., Translation of J. D. van der Waals' “The thermodynamik theory of capillarity under the hypothesis of a continuous variation of density”. Journal of Statistical Physics, 1979. 20(2): p. 197-200.Yang, X., V. Mironov, and Q. Wang, Modeling fusion of cellular aggregates in biofabrication using phase field theories. Journal of theoretical biology, 2012. 303: p. 110-8.Yang, X., Y. Sun, and Q. Wang, A phase field approach for multicellular aggregate fusion in biofabrication. Journal of biomechanical engineering, 2013. 135(7): p. 71005.Flory, P.J., Principles of Polymer Chemistry. 1953, Ithaca, N.Y.: Cornell University Press.Doi, M., Introduction to Polymer Physics, ed. H. See. 1996: Clarendon PressQin, R.S. and H.K. Bhadeshia, Phase field method. Materials Science and Technology, 2010. 26(7): p. 803-811.Aland, S., Modelling of two-phase flow with surface active particles, in Der Fakultät Mathematik und Naturwissenschaften. 2012, Technischen Universität Dresden. p. 127.Chen, L.-Q., Phase-Field Models for Microstructure Evolution. Annual Review of Materials Research, 2002. 32(1): p. 113-140.Folch, R., et al., Phase-field model for Hele-Shaw flows with arbitrary viscosity contrast. I. Theoretical approach. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 1999. 60(2 Pt B): p. 1724-33.Cahn, J.W. and J.E. Hilliard, Free Energy of a Nonuniform System. I. Interfacial Free Energy. The Journal of Chemical Physics, 1958. 28(2): p. 258-267. Bibliografía 227Cahn, J.W. and J.E. Hilliard, Free Energy of a Nonuniform System. III. Nucleation in a Two‐ Component Incompressible Fluid. The Journal of Chemical Physics, 1959. 31(3): p. 688-699.Lervåg, K.Y. and J. Lowengrub, Analysis of the diffuse-domain method for solving PDEs in complex geometries. Communications in mathematical sciences, 2015. 13: p. 1473.Ibrahimi, O.A., et al., Analysis of mutations in fibroblast growth factor (FGF) and a pathogenic mutation in FGF receptor (FGFR) provides direct evidence for the symmetric two-end model for FGFR dimerization. Molecular and cellular biology, 2005. 25(2): p. 671-84.Francavilla, C., et al., Functional Proteomics Defines the Molecular Switch Underlying FGF Receptor Trafficking and Cellular Outputs. Molecular Cell, 2013. 51(6): p. 707-722.Donea, J., et al., Arbitrary Lagrangian–Eulerian Methods, in Encyclopedia of Computational Mechanics. 2004.Iber, D., et al., Simulating tissue morphogenesis and signaling. Methods in molecular biology, 2015. 1189: p. 323-38.Kockelkoren, J., H. Levine, and W.-J. Rappel, Computational approach for modeling intra- and extracellular dynamics. Physical Review E, 2003. 68(3): p. 037702.Kurics, T., D. Menshykau, and D. Iber, Feedback, receptor clustering, and receptor restriction to single cells yield large Turing spaces for ligand-receptor-based Turing models. Physical Review E, 2014. 90(2): p. 022716.Palsson, E. and H.G. Othmer, A model for individual and collective cell movement in Dictyostelium-discoideum. Proceedings of the National Academy of Sciences of the United States of America, 2000. 97(19): p. 10448-10453.Dallon, J.C. and H.G. Othmer, How cellular movement determines the collective force generated by the Dictyostelium discoideum slug. Journal of theoretical biology, 2004. 231(2): p. 203-22.Walker, D.C., et al., The epitheliome: agent-based modelling of the social behaviour of cells. Biosystems, 2004. 76(1-3): p. 89-100.Drasdo, D. and S. Hoehme, A single-cell-based model of tumor growth in vitro: Monolayers and spheroids. Physical biology, 2005. 2: p. 133-47.Chu, Y.S., et al., Johnson-Kendall-Roberts theory applied to living cells. Physical review letters, 2005. 94(2): p. 028102.Hoehme, S. and D. Drasdo, A cell-based simulation software for multi-cellular systems. Bioinformatics, 2010. 26(20): p. 2641-2.Hoehme, S., et al., Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proceedings of the National Academy of Sciences of the United States of America, 2010. 107(23): p. 10371-6.Hoffmann, M., et al., Spatial Organization of Mesenchymal Stem Cells In Vitro—Results from a New Individual Cell-Based Model with Podia. PLOS ONE, 2011. 6(7): p. e21960.Newman, T.J., Modeling Multicellular Systems Using Subcellular Elements. Mathematical Biosciences & Engineering, 2005. 2(3): p. 613-624.Zaman, M.H., et al., Computational model for cell migration in three-dimensional matrices. Biophysical journal, 2005. 89(2): p. 1389-97.Flenner, E., et al., Relating biophysical properties across scales, in Current Topics in Developmental Biology. 2008. p. 461-83.Sandersius, S.A. and T.J. Newman, Modeling cell rheology with the Subcellular Element Model. Physical biology, 2008. 5(1): p. 015002.Kosztin, I., G. Vunjak-Novakovic, and G. Forgacs, Colloquium: Modeling the dynamics of multicellular systems: Application to tissue engineering. Reviews of Modern Physics, 2012. 84(4): p. 1791-1805.259. Chaikin, P.M., Principles of Condensed Matter Physics. 2000: Cambridge University Press.Alberts, B., et al., Molecular Biology of the Cell. 2002, New York: Garland Science.Pathmanathan, P., et al., A computational study of discrete mechanical tissue models. Physical Biology, 2009. 6(3): p. 036001.Phillips, J.C., et al., Scalable molecular dynamics with NAMD. Journal of computational chemistry, 2005. 26(16): p. 1781-802.Shafiee, A., et al., Post-deposition bioink self-assembly: a quantitative study. Biofabrication, 2015. 7(4): p. 045005.Cristea, A. and A. Neagu, Shape changes of bioprinted tissue constructs simulated by the Lattice Boltzmann method. Computers in biology and medicine, 2016. 70: p. 80-87.Silva, H.S. and M.L. Martins, A cellular automata model for cell differentiation. Physica A: Statistical Mechanics and its Applications, 2003. 322: p. 555-566.Garijo, N., et al., Stochastic cellular automata model of cell migration, proliferation and differentiation: Validation with in vitro cultures of muscle satellite cells. Journal of Theoretical Biology, 2012. 314: p. 1-9.Van Scoy, G.K., et al., A cellular automata model of bone formation. Mathematical Biosciences, 2017. 286: p. 58-64.Ben Youssef, B., Simulating Cell-Cell Interactions Using a Multicellular Three-Dimensional Computational Model of Tissue Growth. 2018. p. 215-228.Sipahi, R. and G.K.H. Zupanc, Stochastic cellular automata model of neurosphere growth: Roles of proliferative potential, contact inhibition, cell death, and phagocytosis. Journal of Theoretical Biology, 2018. 445: p. 151-165.Zupanc, G.K.H., F.B. Zupanc, and R. Sipahi, Stochastic cellular automata model of tumorous neurosphere growth: Roles of developmental maturity and cell death. Journal of Theoretical Biology, 2019. 467: p. 100-110.Beros, A., M. Chyba, and K. Noe, Co-evolving cellular automata for morphogenesis. Discrete & Continuous Dynamical Systems - B, 2019. 24(5): p. 2053-2071.Brodland, G.W. and J.H. Veldhuis, Assessing the mechanical energy costs of various tissue reshaping mechanisms. Biomech Model Mechanobiol, 2012. 11(8): p. 1137-47.Steinberg, M.S., Reconstruction of tissues by dissociated cells. Some morphogenetic tissue movements and the sorting out of embryonic cells may have a common explanation. Science, 1963. 141(3579): p. 401-8.Brodland, G.W. and H.H. Chen, The mechanics of heterotypic cell aggregates: insights from computer simulations. J Biomech Eng, 2000. 122(4): p. 402-7.Hwang, M., et al., Rule-Based Simulation of Multi-Cellular Biological Systems-A Review of Modeling Techniques. Cellular and molecular bioengineering, 2009. 2(3): p. 285-294.Rezende, R.A., et al., Organ Printing as an Information Technology. Procedia Engineering, 2015. 110: p. 151-158.Cohen, D.L., et al., Direct freeform fabrication of seeded hydrogels in arbitrary geometries. Tissue Eng, 2006. 12(5): p. 1325-35.Chang, R., J. Nam, and W. Sun, Direct cell writing of 3D microorgan for in vitro pharmacokinetic model. Tissue Eng Part C Methods, 2008. 14(2): p. 157-66.Hopp, B., et al., Survival and proliferative ability of various living cell types after laser-induced forward transfer. Tissue Eng, 2005. 11(11-12): p. 1817-23. Bibliografía 229Mironov, V., V. Kasyanov, and R.R. Markwald, Organ printing: from bioprinter to organ biofabrication line. Curr Opin Biotechnol, 2011. 22(5): p. 667-73.Xu, F., et al., A three-dimensional in vitro ovarian cancer coculture model using a highthroughput cell patterning platform. Biotechnol J, 2011. 6(2): p. 204-212.Jiang, T., et al., Directing the Self-assembly of Tumour Spheroids by Bioprinting Cellular Heterogeneous Models within Alginate/Gelatin Hydrogels. Scientific Reports, 2017. 7(1): p. 4575.Lind, J.U., et al., Instrumented cardiac microphysiological devices via multimaterial threedimensional printing. 2017. 16(3): p. 303-308.Koti, P., et al., Use of GelMA for 3D printing of cardiac myocytes and fibroblasts. Journal of 3D printing in medicine, 2019. 3(1): p. 11-22.Klebe, R.J., Cytoscribing: a method for micropositioning cells and the construction of two- and three-dimensional synthetic tissues. Exp Cell Res, 1988. 179(2): p. 362-73.Nakamura, M., et al., Biocompatible inkjet printing technique for designed seeding of individual living cells. Tissue Eng, 2005. 11(11-12): p. 1658-66.Cui, X., et al., Thermal inkjet printing in tissue engineering and regenerative medicine. Recent Pat Drug Deliv Formul, 2012. 6(2): p. 149-55.Okamoto, T., T. Suzuki, and N. Yamamoto, Microarray fabrication with covalent attachment of DNA using bubble jet technology. Nat Biotechnol, 2000. 18(4): p. 438-41.Matsusaki, M., et al., Three-dimensional human tissue chips fabricated by rapid and automatic inkjet cell printing. Adv Healthc Mater, 2013. 2(4): p. 534-9.Lee, V., et al., Design and fabrication of human skin by three-dimensional bioprinting. Tissue Eng Part C Methods, 2014. 20(6): p. 473-84.Ringeisen, B.R., et al., Laser printing of pluripotent embryonal carcinoma cells. Tissue Eng, 2004. 10(3-4): p. 483-91.Gruene, M., et al., Laser printing of stem cells for biofabrication of scaffold-free autologous grafts. Tissue Eng Part C Methods, 2011. 17(1): p. 79-87.Guillemot, F., et al., High-throughput laser printing of cells and biomaterials for tissue engineering. Acta Biomaterialia, 2010. 6(7): p. 2494-2500.Ali, M., et al., Controlling laser-induced jet formation for bioprinting mesenchymal stem cells with high viability and high resolution. Biofabrication, 2014. 6(4): p. 045001.Stavans, J. and J.A. Glazier, Soap froth revisited: Dynamic scaling in the two-dimensional froth. Phys Rev Lett, 1989. 62(11): p. 1318-1321.Glazier, J.A. and F. Graner, Simulation of the differential adhesion driven rearrangement of biological cells. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, 1993. 47(3): p. 2128-2154.Amar, J.G., The Monte Carlo Method in Science and Engineering. Computing in Science and Engg., 2006. 8(2): p. 9–19.Steinberg, M.S., On the mechanism of tissue reconstruction by dissociated cells, III. Free energy relations and the organization of fused, heteronomic tissue fragments. Proc Natl Acad Sci U S A, 1962. 48(10): p. 1769-76.Steinberg, M.S., Differential adhesion in morphogenesis: a modern view. Curr Opin Genet Dev, 2007. 17(4): p. 281-6.Domansky, K., et al., Perfused multiwell plate for 3D liver tissue engineering. Lab Chip, 2010. 10(1): p. 51-8. 230 Título de la tesis o trabajo de investigaciónCickovski, T.M., et al., A framework for three-dimensional simulation of morphogenesis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2005. 2(4): p. 273-288.Merks, R.M.H. and P. Koolwijk, Modeling Morphogenesis in silico and in vitro: Towards Quantitative, Predictive, Cell-based Modeling. Math. Model. Nat. Phenom., 2009. 4(4): p. 149- 171.R. Chaturvedi, C.H., J. A. Izaguirre, S. A. Newman, J. A. Glazier, M. Alber, A Hybrid Discrete- Continuum Model for 3-D Skeletogenesis of the Vertebrate Limb. International Conference on Cellular Automata, 2004: p. 543-552.Nicholas J.Savill, P., Modelling Morphogenesis: From Single Cells to Crawling Slugs. Journal of Theoretical Biology, 1997. 184(3): p. 229 - 235.Galle, J., et al., Individual cell-based models of tumor-environment interactions: Multiple effects of CD97 on tumor invasion. Am J Pathol, 2006. 169(5): p. 1802-11.Jakab, K., et al., Relating cell and tissue mechanics: implications and applications. Dev Dyn, 2008. 237(9): p. 2438-49.Jakab, K., et al., Organ printing: fiction or science. Biorheology, 2004. 41(3-4): p. 371-5.Yang, X., V. Mironov, and Q. Wang, Modeling fusion of cellular aggregates in biofabrication using phase field theories. J Theor Biol, 2012. 303: p. 110-8.Voter, A.F. INTRODUCTION TO THE KINETIC MONTE CARLO METHOD. 2007. Dordrecht: Springer Netherlands.Glazier James A, A.B.a.N.J.P., Magnetization to Morphogenesis: A Brief History of the Glazier- Graner Hogeweg Model, in Singl-Cell-Based Models in Biology and Medicine, M.A.J.C. A.R.A. Anderson, K.A. Rejniak, Editor. 2007, Mathematics and Biosciences in Interaction: Birkhäuser Verlag Basel / Switzerland. p. 79-106.Steinberg, M.S., Adhesion in development: an historical overview. Dev Biol, 1996. 180(2): p. 377-88.Chatterjee, A. and D.G. Vlachos, An overview of spatial microscopic and accelerated kinetic Monte Carlo methods. Journal of Computer-Aided Materials Design, 2007. 14(2): p. 253-308.Folch, R., et al., Phase-field model for Hele-Shaw flows with arbitrary viscosity contrast. I. Theoretical approach. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, 1999. 60(2 Pt B): p. 1724-33.Yang, X., Y. Sun, and Q. Wang, A phase field approach for multicellular aggregate fusion in biofabrication. J Biomech Eng, 2013. 135(7): p. 71005.Cristea, A. and A. Neagu, Shape changes of bioprinted tissue constructs simulated by the Lattice Boltzmann method. Comput Biol Med, 2016. 70: p. 80-87.Norris, J.R., Markov Chains. Cambridge Series in Statistical and Probabilistic Mathematics. 1997, Cambridge: Cambridge University Press.Feller, W., An Introduction to Probability Theory and Its Applications. Vol. 1. 1966.Blue, J.L., I. Beichl, and F. Sullivan, Faster Monte Carlo simulations. Physical Review E, 1995. 51(2): p. R867-R868.Rahman, T., et al., Atomistic studies of thin film growth. Optical Science and Technology, the SPIE 49th Annual Meeting. Vol. 5509. 2004: SPIE.Trushin, O., et al., Self-learning kinetic Monte Carlo method: Application to Cu(111). Physical Review B, 2005. 72(11): p. 115401.Foty, R.A., et al., Liquid properties of embryonic tissues: Measurement of interfacial tensions. Phys Rev Lett, 1994. 72(14): p. 2298-2301.Freutel, M., et al., Finite element modeling of soft tissues: Material models, tissue interaction and challenges. Clinical Biomechanics, 2014. 29(4): p. 363-372. Bibliografía 231Marmottant, P., et al., The role of fluctuations and stress on the effective viscosity of cell aggregates. Proceedings of the National Academy of Sciences, 2009. 106(41): p. 17271-17275.Schienbein, M., K. Franke, and H. Gruler, Random walk and directed movement: Comparison between inert particles and self-organized molecular machines. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, 1994. 49(6): p. 5462-5471.Kipper, M.J., H.K. Kleinman, and F.W. Wang, New method for modeling connective-tissue cell migration: improved accuracy on motility parameters. Biophys J, 2007. 93(5): p. 1797-808.Mombach, J.C. and J.A. Glazier, Single cell motion in aggregates of embryonic cells. Phys Rev Lett, 1996. 76(16): p. 3032-3035.Flenner, E., et al., Relating biophysical properties across scales. Curr Top Dev Biol, 2008. 81: p. 461-83.Thomas, W.A. and J. Yancey, Can retinal adhesion mechanisms determine cell-sorting patterns: a test of the differential adhesion hypothesis. Development, 1988. 103(1): p. 37-48.Frenkel, J., Viscous flow of crystalline bodies under the action of surface tension. The Journal of Physics, USSR, 1945. 9: p. 385-391.J, D., Eshelby, Trans. AIME, 1949(185).Ma, X., et al., 3D bioprinting of functional tissue models for personalized drug screening and in vitro disease modeling. Adv Drug Deliv Rev, 2018. 132: p. 235-251.An, J., C.K. Chua, and V. Mironov, A Perspective on 4D Bioprinting. International Journal of Bioprinting; Vol 2, No 1 (2016), 2016.Nogueira JA., L.a., Marques TS., Oliveira DS., Mironov V., da Silva and R.R. JV., Simulation of a 3D Bioprinted Human Vascular Segment, in 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, J.K.H.a.R.G. Krist V. Gernaey, Editor. 2015, Elsevier B.V.: Copenhagen, Denmark. p. 684-688Iber, D., et al., Simulating tissue morphogenesis and signaling. Methods Mol Biol, 2015. 1189: p. 323-38.Douglas Brown, R.H., and Wolfgang Christian, Tracker Video Analysis and Modeling Tool. October, 2020.Inc., T.M., Matlab. 2017.Han, Y., et al., Cultivation of recombinant Chinese hamster ovary cells grown as suspended aggregates in stirred vessels. J Biosci Bioeng, 2006. 102(5): p. 430-5.Pan, X., et al., Metabolic characterization of a CHO cell size increase phase in fed-batch cultures. Applied microbiology and biotechnology, 2017. 101(22): p. 8101-8113.EstudiantesInvestigadoresMaestrosPúblico generalLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.unal.edu.co/bitstream/unal/82216/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51ORIGINAL1013662187.2022.pdf1013662187.2022.pdfTesis de Maestría en Ingeniería - Ingeniería Químicaapplication/pdf6429024https://repositorio.unal.edu.co/bitstream/unal/82216/3/1013662187.2022.pdf6c100c60a5389b2461a262ffe303ae0dMD53THUMBNAIL1013662187.2022.pdf.jpg1013662187.2022.pdf.jpgGenerated Thumbnailimage/jpeg5658https://repositorio.unal.edu.co/bitstream/unal/82216/4/1013662187.2022.pdf.jpgf9c6eb0085f1523a48c09eb9da337d55MD54unal/82216oai:repositorio.unal.edu.co:unal/822162023-08-08 23:04:10.265Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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 |