A computational methodology for the generation of genomic maps from fluoroscanning images

ilustraciones, diagramas

Autores:: Ceballos-Arroyo, Alberto Mario

Tipo de recurso:

Fecha de publicación:: 2022

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: eng

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network_acronym_str	UNACIONAL2
network_name_str	Universidad Nacional de Colombia
repository_id_str
dc.title.eng.fl_str_mv	A computational methodology for the generation of genomic maps from fluoroscanning images
dc.title.translated.spa.fl_str_mv	Una metodología computacional para la generación de mapas genómicos a partir de imágenes de Fluoroscanning
title	A computational methodology for the generation of genomic maps from fluoroscanning images
spellingShingle	A computational methodology for the generation of genomic maps from fluoroscanning images 000 - Ciencias de la computación, información y obras generales 570 - Biología::576 - Genética y evolución Mapas Genéticos Biología computacional Genetic maps Computational biology Optical mapping Bioinformatics Genomic mapping Signal processing Image processing DNA Simulations Procesamiento de imágenes ADN Genómica Simulaciones Procesamiento de señales
title_short	A computational methodology for the generation of genomic maps from fluoroscanning images
title_full	A computational methodology for the generation of genomic maps from fluoroscanning images
title_fullStr	A computational methodology for the generation of genomic maps from fluoroscanning images
title_full_unstemmed	A computational methodology for the generation of genomic maps from fluoroscanning images
title_sort	A computational methodology for the generation of genomic maps from fluoroscanning images
dc.creator.fl_str_mv	Ceballos-Arroyo, Alberto Mario
dc.contributor.advisor.none.fl_str_mv	Hernandez Ortiz, Juan Pablo
dc.contributor.author.none.fl_str_mv	Ceballos-Arroyo, Alberto Mario
dc.contributor.researchgroup.spa.fl_str_mv	Crs-Tid Center for Research and Surveillance of Tropical and Infectious Diseases
dc.contributor.orcid.spa.fl_str_mv	Ceballos Arroyo, Alberto Mario [0000-0002-4883-5440]
dc.contributor.googlescholar.spa.fl_str_mv	_zL4pEkAAAAJ
dc.subject.ddc.spa.fl_str_mv	000 - Ciencias de la computación, información y obras generales 570 - Biología::576 - Genética y evolución
topic	000 - Ciencias de la computación, información y obras generales 570 - Biología::576 - Genética y evolución Mapas Genéticos Biología computacional Genetic maps Computational biology Optical mapping Bioinformatics Genomic mapping Signal processing Image processing DNA Simulations Procesamiento de imágenes ADN Genómica Simulaciones Procesamiento de señales
dc.subject.lemb.spa.fl_str_mv	Mapas Genéticos Biología computacional
dc.subject.lemb.eng.fl_str_mv	Genetic maps Computational biology
dc.subject.proposal.eng.fl_str_mv	Optical mapping Bioinformatics Genomic mapping Signal processing Image processing DNA Simulations
dc.subject.proposal.spa.fl_str_mv	Procesamiento de imágenes ADN Genómica Simulaciones Procesamiento de señales
description	ilustraciones, diagramas
publishDate	2022
dc.date.issued.none.fl_str_mv	2022
dc.date.accessioned.none.fl_str_mv	2023-01-31T15:49:30Z
dc.date.available.none.fl_str_mv	2023-01-31T15:49:30Z
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	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/83214
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/83214 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	Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2008). Molecular Biology of the Cell (M. Anderson & S. Granum, Eds.; 5th). Garland Science. Aston, C., Hiort, C., & Schwartz, D. C. (1999). Optical Mapping: An Approach for Fine Mapping. Methods Enzymol., 303, 55–73. https://doi.org/10.1016/S0076-6879(99) 03006-2 Bahadar, K., Khaliq, A. A., & Shahid, M. (2016). A morphological hessian based approach for retinal blood vessels segmentation and denoising using region based otsu thresholding. PLoS One, 11 (7), 1–19. https://doi.org/10.1371/journal.pone.0158996 Barber, D. (2012). Bayesian Reasoning and Machine Learning. Cambridge University Press. https://doi.org/10.1017/CBO9780511804779 Bennink, M., Sch ̈arer, O., Kanaar, R., Sakata-Sogawa, K., Schins, J., Kanger, J., de Grooth, B., & Greve, J. (1999). Single-molecule manipulation of double-stranded dna using optical tweezers: Interaction studies of dna with reca and yoyo-1. Cytometry, 36 (3), 200–208. Borst, A., & Theunissen, F. E. (1999). Information theory and neural coding. Nat Neurosci, 2 (11), 947–957. https://doi.org/10.1038/14731 Brady, E. (1992). Real-time data compression using a FFT digital signal processor. https://doi.org/10.2172/7275570 Cao, H., Hastie, A. R., Cao, D., Lam, E. T., Sun, Y., Huang, H., Liu, X., Lin, L., Andrews, W., Chan, S., Huang, S., Tong, X., Requa, M., Anantharaman, T., Krogh, A., Yang, H., Cao, H., & Xu, X. (2014). Rapid detection of structural variation in a human genome using nanochannel-based genome mapping technology. Gigascience, 3 (1), 1–11. https://doi.org/10.1186/2047-217X-3-34 Chan, E. K., Cameron, D. L., Petersen, D. C., Lyons, R. J., Baldi, B. F., Papenfuss, A. T., Thomas, D. M., & Hayes, V. M. (2018). Optical mapping reveals a higher level of genomic architecture of chained fusions in cancer. Genome Research, 28 (5), 726–738. https://doi.org/10.1101/gr.227975.117 Chandra, R., Dagum, L., Kohr, D., Menon, R., Maydan, D., & McDonald, J. (2001). Parallel programming in OpenMP (D. E. Penrose & E. Wade, Eds.; 1st). Morgan Kaufmann Publishers. Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., Xie, W., Rosen, G. L., Lengerich, B. J., Israeli, J., Lanchantin, J., Woloszynek, S., Carpenter, A. E., Shrikumar, A., Xu, J., . . . Greene, C. S. (2018). Opportunities and obstacles for deep learning in biology and medicine. Journal of The Royal Society Interface, 15 (141), 0170387. https://doi.org/10.1098/rsif.2017.0387 Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2001). Introduction to Algorithms (2nd). The MIT Press; McGraw-Hill Book Company. DeGroot, M. H., Schervish, M. J., & Sheet, C. (2011). Probability and Statistics. Addison Wesley. https://doi.org/0321709705 Deligeorgiev, T., Kaloyanova, S., & Vaquero, J. (2010). Intercalating cyanine dyes for nucleic acid detection. Recent Patents on Materials Science, 2, 1–26. https://doi.org/10.2174/1874465610902010001 Dimalanta, E. T., Lim, A., Runnheim, R., Lamers, C., Churas, C., Forrest, D. K., Pablo, J. J. D., Graham, M. D., Coppersmith, S. N., Goldstein, S., & Schwartz, D. C. (2004). A Microfluidic System for Large DNA Molecule Arrays. Anal. Chem., 76 (18), 5293–5301. https://doi.org/10.1021/ac0496401 Duarte, M. (2021). Detecta: A python module to detect events in data (Version v0.0.5). Zenodo. https://doi.org/10.5281/zenodo.4598962 Dvirnas, A., Pichler, C., Stewart, C. L., Quaderi, S., Nyberg, L. K., M ̈uller, V., Bikkarolla, S. K., Kristiansson, E., Sandegren, L., Westerlund, F., & Ambj ̈ornsson, T. (2018).Facilitated sequence assembly using densely labeled optical DNA barcodes: A combinatorial auction approach. PLOS ONE, 13 (3), e0193900. https://doi.org/10.1371/journal.pone.0193900 Gonzalez, R. C., & Woods, R. E. (2008). Digital image processing (3rd). Prentice Hall. https://www.imageprocessingplace.com Guennebaud, G., & Jacob, B. (2010). Eigen v3 [software library]. http://eigen.tuxfamily.org Guizar-Sicairos, M., Thurman, S. T., & Fienup, J. R. (2008). Efficient subpixel image registration algorithms. Opt. Lett., 33 (2), 156–158. https://doi.org/10.1364/OL.33.000156 G ̈unther, K., Mertig, M., & Seidel, R. (2010). Mechanical and structural properties of YOYO-1 complexed DNA. Nucleic Acids Res., 38 (19), 6526–6532. https://doi.org/10.1093/nar/gkq434 Gupta, A., Kounovsky-Shafer, K. L., Ravindran, P., & Schwartz, D. C. (2016). Optical mapping and nanocoding approaches to whole-genome analysis. Microfluid. Nanofluidics, 20 (3), 1–14. https://doi.org/10.1007/s10404-015-1685-y Gupta, A., Place, M., Goldstein, S., Sarkar, D., Zhou, S., Potamousis, K., Kim, J., Flanagan, C., Li, Y., Newton, M. A., Callander, N. S., Hematti, P., Bresnick, E. H., Ma, J., Asimakopoulos, F., & Schwartz, D. C. (2015). Single-molecule analysis reveals widespread structural variation in multiple myeloma. Proc. Natl. Acad. Sci., 112 (25), 7689–7694. https://doi.org/10.1073/pnas.1418577112 Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del R ́ıo, J. F., Wiebe, M., Peterson, P., . . . Oliphant, T. E. (2020). Array programming with NumPy. Nature, 585 (7825), 357–362. https://doi.org/10.1038/s41586-020-2649-2 International Organization for Standardization. (2012). ISO/IEC 14882:2011 Information technology — Programming languages — C++. Geneva, Switzerland, International Organization for Standardization. http://www.iso.org/iso/iso catalogue/catalogue_tc/catalogue detail.htm?csnumber=50372 Jo, K., Schramm, T. M., & Schwartz, D. C. (2009). A single-molecule barcoding system using nanoslits for DNA analysis : nanocoding. Methods Mol. Biol., 544 (8), 29–42. https://doi.org/10.1007/978-1-59745-483-4_3 Johansen, F., & Jacobsen, J. P. (1998). 1H NMR studies of the bis-intercalation of a homodimeric oxazole yellow dye in DNA oligonucleotides. J Biomol Struct Dyn, 16 (2), 205–222. Johnson, I. (2010). Molecular probes handbook: A guide to fluorescent probes and labeling technologies. Life Technologies Corporation. https://books.google.com/books?id=djuacQAACAAJ Katsonis, P., Koire, A., Wilson, S. J., Hsu, T. K., Lua, R. C., Wilkins, A. D., & Lichtarge, O. (2014). Single nucleotide variations: Biological impact and theoretical interpretation. Protein Sci., 23 (12), 1650–1666. https://doi.org/10.1002/pro.2552 Kounovsky-Shafer, K. L., Hernandez-Ortiz, J. P., Potamousis, K., Tsvid, G., Place, M., Ravindran, P., Jo, K., Zhou, S., Odijk, T., de Pablo, J. J., & Schwartz, D. C. (2017). Electrostatic confinement and manipulation of DNA molecules for genome analysis. Proc. Natl. Acad. Sci., (January), 13400–13405. https : / / doi . org / 10 . 1073 / pnas . 1711069114 Larsson, A., Carlsson, C., Jonsson, M., & Albinsson, B. (1994). Characterization of the Bind- ing of the Fluorescent Dyes YO and YOYO to DNA by Polarized Light Spectroscopy. J. Am. Chem. Soc., 116 (19), 8459–8465. https://doi.org/10.1021/ja00098a004 Lee, S., & Jo, K. (2016). Visualization of Surface-tethered Large DNA Molecules with a Fluorescent Protein DNA Binding Peptide. Journal of Visualized Experiments: JoVE, (112). https://doi.org/10.3791/54141 Lee, S., Lee, Y., Kim, Y., Wang, C., Park, J., Jung, G. Y., Chen, Y.-L., Chang, R., Ikeda, S., Sugiyama, H., & Jo, K. (2018). Nanochannel-Confined TAMRA-Polypyrrole Stained DNA Stretching by Varying the Ionic Strength from Micromolar to Millimolar Con- centrations. Polymers, 11 (1), 15. https://doi.org/10.3390/polym11010015 Lesho, E., Clifford, R., Onmus-Leone, F., Appalla, L., Snesrud, E., Kwak, Y., Ong, A., May- bank, R., Waterman, P., Rohrbeck, P., Julius, M., Roth, A., Martinez, J., Nielsen, L., Steele, E., McGann, P., & Hinkle, M. (2016). The challenges of implementing next generation sequencing across a large healthcare system, and the molecular epidemiology and antibiotic susceptibilities of carbapenemase-producing bacteria in the healthcare system of the U.S. Department of Defense. PLoS One, 11 (5), 1–12. https: //doi.org/10.1371/journal.pone.0155770 Leung, A. K. Y., Kwok, T. P., Wan, R., Xiao, M., Kwok, P. Y., Yip, K. Y., & Chan, T. F. (2017). OMBlast: Alignment tool for optical mapping using a seed-and-extend approach. Bioinformatics, 33 (3), 311–319. https://doi.org/10.1093/bioinformatics/ btw620 Li, Y., Zhou, S., Schwartz, D. C., & Ma, J. (2016). Allele-Specific Quantification of Structural Variations in Cancer Genomes. Cell Systems, 3 (1), 21–34. https://doi.org/10.1016/j.cels.2016.05.007 Louie, E., Ott, J., & Majewski, J. (2003). Nucleotide Frequency Variation Across Human Genes. Genome Res., 2594–2601. https://doi.org/10.1101/gr.1317703. Majewski, J., Majewski, J., Ott, J., & Ott, J. (2002). Distribution and characterization of regulatory elements in the human genome. Genome Res., 12 (212), 1827–1836. https: //doi.org/10.1101/gr.606402.12 Marie, R., Pedersen, J. N., Bauer, D. L., Rasmussen, K. H., Yusuf, M., Volpi, E., Flyvbjerg, H., Kristensen, A., & Mir, K. U. (2013). Integrated view of genome structure and sequence of a single DNA molecule in a nanofluidic device. Proceedings of the National Academy of Sciences of the United States of America, 110 (13), 4893–4898. https://doi.org/10.1073/pnas.1214570110 Marie, R., Pedersen, J. N., Bærlocher, L., Koprowska, K., Pødenphant, M., Sabatel, C., Za- lkovskij, M., Mironov, A., Bilenberg, B., Ashley, N., Flyvbjerg, H., Bodmer, W. F., Kristensen, A., & Mir, K. U. (2018). Single-molecule DNA-mapping and whole-genome sequencing of individual cells. Proceedings of the National Academy of Sciences of the United States of America, 115 (44), 11192–11197. https://doi.org/10.1073/pnas.1804194115 Matsumoto, M., & Nishimura, T. (1998). Mersenne twister: A 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Trans. on Modeling and Computer Simulation, 8 (1), 3–30. Min, S., Lee, B., & Yoon, S. (2017). Deep learning in bioinformatics. Brief. Bioinform., 18 (5), arXiv 1603.06430, 851–869. https://doi.org/10.1093/bib/bbw068 M ̈uller, V., Dvirnas, A., Andersson, J., Singh, V., KK, S., Johansson, P., Ebenstein, Y., Ambj ̈ornsson, T., & Westerlund, F. (2019). Enzyme-free optical DNA mapping of the human genome using competitive binding. Nucleic Acids Research, 47 (15), e89. https://doi.org/10.1093/nar/gkz489 Nagarajan, N., Read, T. D., & Pop, M. (2008). Scaffolding and validation of bacterial genome assemblies using optical restriction maps. Bioinformatics, 24 (10), 1229–1235. https://doi.org/10.1093/bioinformatics/btn102 Nandi, S. (2017). Statistical Learning Methods for Fluroroscanning (Ph.D. Thesis). University of Wisconsin-Madison. Netzel, T. L., Nafisi, K., Zhao, M., Lenhard, J. R., & Johnson, I. (1995). Base-Content Dependence of Emission Enhancements, Quantum Yields, and Lifetimes for Cyanine Dyes Bound to Double-Strand DNA: Photophysical Properties of Monomeric and Bichromomphoric DNA Stains. J. Phys. Chem., 99 (51), 17936–17947. https://doi.org/10.1021/j100051a019 Nyberg, L., Persson, F., ̊Akerman, B., & Westerlund, F. (2013). Heterogeneous staining: a tool for studies of how fluorescent dyes affect the physical properties of DNA. Nucleic Acids Research, 41 (19), e184–e184. https://doi.org/10.1093/nar/gkt755 Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9 (1), 62–66. https://doi.org/ 10 .1109/TSMC.1979.4310076 Park, J., Lee, S., Won, N., Shin, E., Kim, S.-H., Chun, M.-Y., Gu, J., Jung, G.-Y., Lim, K.-I., & Jo, K. (2019). Single-molecule DNA visualization using AT-specific red and non-specific green DNA-binding fluorescent proteins. Analyst, 144 (3), 921–927. https://doi.org/10.1039/C8AN01426D Pereira, R., Couto, M., Ribeiro, F., Rua, R., Cunha, J., Fernandes, J. P., & Saraiva, J. (2021). Ranking programming languages by energy efficiency. Science of Computer Programming, 205, 102609. https://doi.org/https://doi.org/10.1016/j.scico.2021. 102609 Precision Medicine Initiative (PMI) Working Group. (2015). The precision medicine initia- tive cohort program – building a research foundation for 21st century medicine (tech.rep.). http://www.nih.gov/precisionmedicine Ravindran, P., & Gupta, A. (2015). Image processing for optical mapping. Gigascience, 4 (1), 1–8. https://doi.org/10.1186/s13742-015-0096-z Reisner, W., Larsen, N. B., Silahtaroglu, A., Kristensen, A., Tommerup, N., Tegenfeldt, J. O., & Flyvbjerg, H. (2010). Single-molecule denaturation mapping of DNA in nanofluidic channels. Proceedings of the National Academy of Sciences, 107 (30), 13294–13299. https://doi.org/10.1073/pnas.1007081107 Roy, A., Diao, Y., Evani, U., Abhyankar, A., Howarth, C., Le Priol, R., & Bloom, T. (2017). Massively Parallel Processing of Whole Genome Sequence Data, In Proc. 2017 acm int. conf. manag. data - sigmod ’17. https://doi.org/10.1145/3035918.3064048 Rye, H. S., Yue, S., Wemmer, D. E., Quesada, M. A., Haugland, R. P., Mathies, R. A., & Glazer, A. N. (1992). Stable fluorescent complexes of double-stranded DNA with bis-intercalating asymmetric cyanine dyes: Properties and applications. Nucleic Acids Research, 20 (11), 2803–2812. Schwartz, D., Li, X., Hernandez, L., Ramnarain, S., Huff, E., & Wang, Y. (1993). Ordered restriction maps of Saccharomyces cerevisiae chromosomes constructed by optical mapping. Science 262 (5130), 110–114. https://doi.org/10.1126/science. 8211116 Shapiro, H. (2004). Excitation and emission spectra of common dyes. Current Protocols in Cytometry, Chapter 1, Unit 1.19. https://doi.org/10.1002/0471142956.cy0119s26 Shiguo, Z., Herscheleb, J., & Schwartz, D. C. (2007). A single molecule system for whole genome analysis., In New high throughput technol. dna seq. genomics. Shit, S., Paetzold, J. C., Sekuboyina, A., Zhylka, A., Ezhov, I., Unger, A., Pluim, J. P. W., Tetteh, G., & Menze, B. H. (2020). clDice – a Topology-Preserving Loss Function for Tubular Structure Segmentation, arXiv 2003.07311, 1–23. http://arxiv.org/abs/ 2003.07311 Spielmann, H. P., Wemmer, D. E., & Jacobsen, J. P. (1995). Solution structure of a DNA complex with the fluorescent bis-intercalator TOTO determined by NMR spectroscopy. Biochemistry, 34 (27), 8542–8553. Tang, H., Lyons, E., & Town, C. D. (2015). Optical mapping in plant comparative genomics. Gigascience, 4 (1), 1–6. https://doi.org/10.1186/s13742-015-0044-y Teague, B., Waterman, M. S., Goldstein, S., Potamousis, K., Zhou, S., Reslewic, S., Sarkar, D., Valouev, A., Churas, C., Kidd, J. M., Kohn, S., Runnheim, R., Lamers, C., Forrest, D., Newton, M. A., Eichler, E. E., Kent-First, M., Surti, U., Livny, M., & Schwartz, D. C. (2010). High-resolution human genome structure by single-molecule analysis. Proc. Natl. Acad. Sci., 107 (24), 10848–10853. https://doi.org/10.1073/ pnas.0914638107 Valouev, A., Schwartz, D. C., Zhou, S., & Waterman, M. S. (2006). An algorithm for assembly of ordered restriction maps from single DNA molecules. Proc. Natl. Acad. Sci., 103 (43), 15770–15775. https://doi.org/10.1073/pnas.0604040103 Valouev, A., Li, L., Liu, Y.-C., Schwartz, D. C., Yang, Y., Zhang, Y., & Waterman, M. S. (2006). Alignment of Optical Maps. J. Comput. Biol., 13 (2), 442–462. https://doi. org/10.1089/cmb.2006.13.442 Valouev, A., Zhang, Y., Schwartz, D. C., & Waterman, M. S. (2006). Refinement of optical map assemblies. Bioinformatics, 22 (10), 1217–1224. https://doi.org/10.1093/ bioinformatics/btl063 Van der Walt, S., Sch ̈onberger, J. L., Nunez-Iglesias, J., Boulogne, F., Warner, J. D., Yager, N., Gouillart, E., & Yu, T. (2014). Scikit-image: Image processing in python. PeerJ, 2, e453. Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., . . . SciPy 1.0 Contributors. (2020). SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17, 261–272. https://doi.org/ 10.1038/s41592-019-0686-2 Voigtl ̈ander, B. (2015). Data Representation and Image Processing (P. Avouris, B. Bhushan, D. Bimberg, H. Sakaki, K. von Klitzing, & R. Wiesendanger, Eds.; 1st ed.). In P. Avouris, B. Bhushan, D. Bimberg, H. Sakaki, K. von Klitzing, & R. Wiesendanger (Eds.), Scanning probe microsc. at. force microsc. scanning tunneling microsc. (1st ed.). Berlin, Heidelberg, Springer-Verlag GmbH Berlin Heidelberg. https://doi.org/10.1016/B978-0-12-814182-3.00005-5 Zhou, S., & Schwartz, D. C. (2004). The Optical Mapping of Microbial Genomes. ASM News, 70 (7), 323–330.
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spelling	Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Hernandez Ortiz, Juan Pablo8fa9fb9ff30808928505283b2b0a61e2Ceballos-Arroyo, Alberto Mario4ad50f648a7028088c8472758b716574600Crs-Tid Center for Research and Surveillance of Tropical and Infectious DiseasesCeballos Arroyo, Alberto Mario [0000-0002-4883-5440]_zL4pEkAAAAJ2023-01-31T15:49:30Z2023-01-31T15:49:30Z2022https://repositorio.unal.edu.co/handle/unal/83214Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasFluoroscanning is a novel system for quickly generating genomic maps. Unlike preceding systems like optical mapping and nanocoding, Fluoroscanning relies only on the intensity signals produced by dye fluorochromes when bound to DNA nucleotides, which we deem Fluoroscans. As part of this work, we wanted to develop and evaluated a fast digital image processing pipeline for extracting Fluoroscan signals from fluorescence microscopy images, to devise and implement a parallel and highly optimized algorithm for simulating the physical principles behind Fluoroscanning, and to guide laboratory experiments using such a tool in order to enable the generation of genomic maps through alignment algorithms. As a result of our work, we were able to set up a workflow in which real Fluoroscans extracted from digital images were used to adjust the parameters of a Monte Carlo simulation of Fluoroscanning which was then leveraged to guide further laboratory experiments and to generate a synthetic human-genome-scale dataset which will enable the development of signal alignment algorithms for genomic map generation.El Fluoroscanning es un sistema novedoso para la generación rápida de mapas genómicos. A diferencia de sistemas anteriores como el optical mapping y el nanocoding, el Fluoroscanning solo se basa en la intensidad de las señales (que llamamos Fluoroscans) producidas por fluorocromos de tinte cuando se adhieren a nucleótidos de ADN. Como parte de este trabajo, se desarrolla y se evalúa una serie de pasos que incluyen procesamiento de imágenes para extraer señales Fluoroscan de manera rápida a partir de imágenes de microscopía de fluorescencia, un algoritmo paralelo y altamente optimizado para simular los principios físicos detrás del Fluoroscanning y una metodología para guiar experimentos de laboratorio a partir de dicho algoritmo. Como resultado de nuestro trabajo, pudimos establecer un flujo de trabajo en el que Fluoroscans reales extraídos de imágenes digitales se utilizaron para ajustar los parámetros de las simulaciones, que a su vez fueron utilizadas para guiar experimentos de laboratorio y para generar un conjunto de datos sintético a escala genómica que permitirá ayudar al desarrollo de algoritmos de alineamiento de señales para la generación de mapas genómicos. (Texto tomado de la fuente)MaestríaMagíster en Ingeniería - Ingeniería de SistemasBioinformáticaVisión ArtificialBiología computacionalÁrea Curricular de Ingeniería de Sistemas e Informáticavii, 72 páginasapplication/pdfengUniversidad Nacional de ColombiaMedellín - Minas - Maestría en Ingeniería - Ingeniería de SistemasFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín000 - Ciencias de la computación, información y obras generales570 - Biología::576 - Genética y evoluciónMapas GenéticosBiología computacionalGenetic mapsComputational biologyOptical mappingBioinformaticsGenomic mappingSignal processingImage processingDNASimulationsProcesamiento de imágenesADNGenómicaSimulacionesProcesamiento de señalesA computational methodology for the generation of genomic maps from fluoroscanning imagesUna metodología computacional para la generación de mapas genómicos a partir de imágenes de FluoroscanningTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMRedColLaReferenciaAlberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2008). Molecular Biology of the Cell (M. Anderson & S. Granum, Eds.; 5th). Garland Science.Aston, C., Hiort, C., & Schwartz, D. C. (1999). Optical Mapping: An Approach for Fine Mapping. Methods Enzymol., 303, 55–73. https://doi.org/10.1016/S0076-6879(99) 03006-2Bahadar, K., Khaliq, A. A., & Shahid, M. (2016). A morphological hessian based approach for retinal blood vessels segmentation and denoising using region based otsu thresholding. PLoS One, 11 (7), 1–19. https://doi.org/10.1371/journal.pone.0158996Barber, D. (2012). Bayesian Reasoning and Machine Learning. Cambridge University Press. https://doi.org/10.1017/CBO9780511804779Bennink, M., Sch ̈arer, O., Kanaar, R., Sakata-Sogawa, K., Schins, J., Kanger, J., de Grooth, B., & Greve, J. (1999). Single-molecule manipulation of double-stranded dna using optical tweezers: Interaction studies of dna with reca and yoyo-1. Cytometry, 36 (3), 200–208.Borst, A., & Theunissen, F. E. (1999). Information theory and neural coding. Nat Neurosci, 2 (11), 947–957. https://doi.org/10.1038/14731Brady, E. (1992). Real-time data compression using a FFT digital signal processor. https://doi.org/10.2172/7275570Cao, H., Hastie, A. R., Cao, D., Lam, E. T., Sun, Y., Huang, H., Liu, X., Lin, L., Andrews, W., Chan, S., Huang, S., Tong, X., Requa, M., Anantharaman, T., Krogh, A., Yang, H., Cao, H., & Xu, X. (2014). Rapid detection of structural variation in a human genome using nanochannel-based genome mapping technology. Gigascience, 3 (1), 1–11. https://doi.org/10.1186/2047-217X-3-34Chan, E. K., Cameron, D. L., Petersen, D. C., Lyons, R. J., Baldi, B. F., Papenfuss, A. T., Thomas, D. M., & Hayes, V. M. (2018). Optical mapping reveals a higher level of genomic architecture of chained fusions in cancer. Genome Research, 28 (5), 726–738. https://doi.org/10.1101/gr.227975.117Chandra, R., Dagum, L., Kohr, D., Menon, R., Maydan, D., & McDonald, J. (2001). Parallel programming in OpenMP (D. E. Penrose & E. Wade, Eds.; 1st). Morgan Kaufmann Publishers.Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., Xie, W., Rosen, G. L., Lengerich, B. J., Israeli, J., Lanchantin, J., Woloszynek, S., Carpenter, A. E., Shrikumar, A., Xu, J., . . . Greene, C. S. (2018). Opportunities and obstacles for deep learning in biology and medicine. Journal of The Royal Society Interface, 15 (141), 0170387. https://doi.org/10.1098/rsif.2017.0387Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2001). Introduction to Algorithms (2nd). The MIT Press; McGraw-Hill Book Company.DeGroot, M. H., Schervish, M. J., & Sheet, C. (2011). Probability and Statistics. Addison Wesley. https://doi.org/0321709705Deligeorgiev, T., Kaloyanova, S., & Vaquero, J. (2010). Intercalating cyanine dyes for nucleic acid detection. Recent Patents on Materials Science, 2, 1–26. https://doi.org/10.2174/1874465610902010001Dimalanta, E. T., Lim, A., Runnheim, R., Lamers, C., Churas, C., Forrest, D. K., Pablo, J. J. D., Graham, M. D., Coppersmith, S. N., Goldstein, S., & Schwartz, D. C. (2004). A Microfluidic System for Large DNA Molecule Arrays. Anal. Chem., 76 (18), 5293–5301. https://doi.org/10.1021/ac0496401Duarte, M. (2021). Detecta: A python module to detect events in data (Version v0.0.5). Zenodo. https://doi.org/10.5281/zenodo.4598962Dvirnas, A., Pichler, C., Stewart, C. L., Quaderi, S., Nyberg, L. K., M ̈uller, V., Bikkarolla, S. K., Kristiansson, E., Sandegren, L., Westerlund, F., & Ambj ̈ornsson, T. (2018).Facilitated sequence assembly using densely labeled optical DNA barcodes: A combinatorial auction approach. PLOS ONE, 13 (3), e0193900. https://doi.org/10.1371/journal.pone.0193900Gonzalez, R. C., & Woods, R. E. (2008). Digital image processing (3rd). Prentice Hall. https://www.imageprocessingplace.comGuennebaud, G., & Jacob, B. (2010). Eigen v3 [software library]. http://eigen.tuxfamily.orgGuizar-Sicairos, M., Thurman, S. T., & Fienup, J. R. (2008). Efficient subpixel image registration algorithms. Opt. Lett., 33 (2), 156–158. https://doi.org/10.1364/OL.33.000156G ̈unther, K., Mertig, M., & Seidel, R. (2010). Mechanical and structural properties of YOYO-1 complexed DNA. Nucleic Acids Res., 38 (19), 6526–6532. https://doi.org/10.1093/nar/gkq434Gupta, A., Kounovsky-Shafer, K. L., Ravindran, P., & Schwartz, D. C. (2016). Optical mapping and nanocoding approaches to whole-genome analysis. Microfluid. Nanofluidics, 20 (3), 1–14. https://doi.org/10.1007/s10404-015-1685-yGupta, A., Place, M., Goldstein, S., Sarkar, D., Zhou, S., Potamousis, K., Kim, J., Flanagan, C., Li, Y., Newton, M. A., Callander, N. S., Hematti, P., Bresnick, E. H., Ma, J., Asimakopoulos, F., & Schwartz, D. C. (2015). Single-molecule analysis reveals widespread structural variation in multiple myeloma. Proc. Natl. Acad. Sci., 112 (25), 7689–7694. https://doi.org/10.1073/pnas.1418577112Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del R ́ıo, J. F., Wiebe, M., Peterson, P., . . . Oliphant, T. E. (2020). Array programming with NumPy. Nature, 585 (7825), 357–362. https://doi.org/10.1038/s41586-020-2649-2International Organization for Standardization. (2012). ISO/IEC 14882:2011 Information technology — Programming languages — C++. Geneva, Switzerland, International Organization for Standardization. http://www.iso.org/iso/iso catalogue/catalogue_tc/catalogue detail.htm?csnumber=50372Jo, K., Schramm, T. M., & Schwartz, D. C. (2009). A single-molecule barcoding system using nanoslits for DNA analysis : nanocoding. Methods Mol. Biol., 544 (8), 29–42. https://doi.org/10.1007/978-1-59745-483-4_3Johansen, F., & Jacobsen, J. P. (1998). 1H NMR studies of the bis-intercalation of a homodimeric oxazole yellow dye in DNA oligonucleotides. J Biomol Struct Dyn, 16 (2), 205–222.Johnson, I. (2010). Molecular probes handbook: A guide to fluorescent probes and labeling technologies. Life Technologies Corporation. https://books.google.com/books?id=djuacQAACAAJKatsonis, P., Koire, A., Wilson, S. J., Hsu, T. K., Lua, R. C., Wilkins, A. D., & Lichtarge, O. (2014). Single nucleotide variations: Biological impact and theoretical interpretation. Protein Sci., 23 (12), 1650–1666. https://doi.org/10.1002/pro.2552Kounovsky-Shafer, K. L., Hernandez-Ortiz, J. P., Potamousis, K., Tsvid, G., Place, M., Ravindran, P., Jo, K., Zhou, S., Odijk, T., de Pablo, J. J., & Schwartz, D. C. (2017). Electrostatic confinement and manipulation of DNA molecules for genome analysis. Proc. Natl. Acad. Sci., (January), 13400–13405. https : / / doi . org / 10 . 1073 / pnas . 1711069114Larsson, A., Carlsson, C., Jonsson, M., & Albinsson, B. (1994). Characterization of the Bind- ing of the Fluorescent Dyes YO and YOYO to DNA by Polarized Light Spectroscopy. J. Am. Chem. Soc., 116 (19), 8459–8465. https://doi.org/10.1021/ja00098a004Lee, S., & Jo, K. (2016). Visualization of Surface-tethered Large DNA Molecules with a Fluorescent Protein DNA Binding Peptide. Journal of Visualized Experiments: JoVE, (112). https://doi.org/10.3791/54141Lee, S., Lee, Y., Kim, Y., Wang, C., Park, J., Jung, G. Y., Chen, Y.-L., Chang, R., Ikeda, S., Sugiyama, H., & Jo, K. (2018). Nanochannel-Confined TAMRA-Polypyrrole Stained DNA Stretching by Varying the Ionic Strength from Micromolar to Millimolar Con- centrations. Polymers, 11 (1), 15. https://doi.org/10.3390/polym11010015Lesho, E., Clifford, R., Onmus-Leone, F., Appalla, L., Snesrud, E., Kwak, Y., Ong, A., May- bank, R., Waterman, P., Rohrbeck, P., Julius, M., Roth, A., Martinez, J., Nielsen, L., Steele, E., McGann, P., & Hinkle, M. (2016). The challenges of implementing next generation sequencing across a large healthcare system, and the molecular epidemiology and antibiotic susceptibilities of carbapenemase-producing bacteria in the healthcare system of the U.S. Department of Defense. PLoS One, 11 (5), 1–12. https: //doi.org/10.1371/journal.pone.0155770Leung, A. K. Y., Kwok, T. P., Wan, R., Xiao, M., Kwok, P. Y., Yip, K. Y., & Chan, T. F. (2017). OMBlast: Alignment tool for optical mapping using a seed-and-extend approach. Bioinformatics, 33 (3), 311–319. https://doi.org/10.1093/bioinformatics/ btw620Li, Y., Zhou, S., Schwartz, D. C., & Ma, J. (2016). Allele-Specific Quantification of Structural Variations in Cancer Genomes. Cell Systems, 3 (1), 21–34. https://doi.org/10.1016/j.cels.2016.05.007Louie, E., Ott, J., & Majewski, J. (2003). Nucleotide Frequency Variation Across Human Genes. Genome Res., 2594–2601. https://doi.org/10.1101/gr.1317703.Majewski, J., Majewski, J., Ott, J., & Ott, J. (2002). Distribution and characterization of regulatory elements in the human genome. Genome Res., 12 (212), 1827–1836. https: //doi.org/10.1101/gr.606402.12Marie, R., Pedersen, J. N., Bauer, D. L., Rasmussen, K. H., Yusuf, M., Volpi, E., Flyvbjerg, H., Kristensen, A., & Mir, K. U. (2013). Integrated view of genome structure and sequence of a single DNA molecule in a nanofluidic device. Proceedings of the National Academy of Sciences of the United States of America, 110 (13), 4893–4898. https://doi.org/10.1073/pnas.1214570110Marie, R., Pedersen, J. N., Bærlocher, L., Koprowska, K., Pødenphant, M., Sabatel, C., Za- lkovskij, M., Mironov, A., Bilenberg, B., Ashley, N., Flyvbjerg, H., Bodmer, W. F., Kristensen, A., & Mir, K. U. (2018). Single-molecule DNA-mapping and whole-genome sequencing of individual cells. Proceedings of the National Academy of Sciences of the United States of America, 115 (44), 11192–11197. https://doi.org/10.1073/pnas.1804194115Matsumoto, M., & Nishimura, T. (1998). Mersenne twister: A 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Trans. on Modeling and Computer Simulation, 8 (1), 3–30.Min, S., Lee, B., & Yoon, S. (2017). Deep learning in bioinformatics. Brief. Bioinform., 18 (5), arXiv 1603.06430, 851–869. https://doi.org/10.1093/bib/bbw068M ̈uller, V., Dvirnas, A., Andersson, J., Singh, V., KK, S., Johansson, P., Ebenstein, Y., Ambj ̈ornsson, T., & Westerlund, F. (2019). Enzyme-free optical DNA mapping of the human genome using competitive binding. Nucleic Acids Research, 47 (15), e89. https://doi.org/10.1093/nar/gkz489Nagarajan, N., Read, T. D., & Pop, M. (2008). Scaffolding and validation of bacterial genome assemblies using optical restriction maps. Bioinformatics, 24 (10), 1229–1235. https://doi.org/10.1093/bioinformatics/btn102Nandi, S. (2017). Statistical Learning Methods for Fluroroscanning (Ph.D. Thesis). University of Wisconsin-Madison.Netzel, T. L., Nafisi, K., Zhao, M., Lenhard, J. R., & Johnson, I. (1995). Base-Content Dependence of Emission Enhancements, Quantum Yields, and Lifetimes for Cyanine Dyes Bound to Double-Strand DNA: Photophysical Properties of Monomeric and Bichromomphoric DNA Stains. J. Phys. Chem., 99 (51), 17936–17947. https://doi.org/10.1021/j100051a019Nyberg, L., Persson, F., ̊Akerman, B., & Westerlund, F. (2013). Heterogeneous staining: a tool for studies of how fluorescent dyes affect the physical properties of DNA. Nucleic Acids Research, 41 (19), e184–e184. https://doi.org/10.1093/nar/gkt755Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9 (1), 62–66. https://doi.org/ 10 .1109/TSMC.1979.4310076Park, J., Lee, S., Won, N., Shin, E., Kim, S.-H., Chun, M.-Y., Gu, J., Jung, G.-Y., Lim, K.-I., & Jo, K. (2019). Single-molecule DNA visualization using AT-specific red and non-specific green DNA-binding fluorescent proteins. Analyst, 144 (3), 921–927. https://doi.org/10.1039/C8AN01426DPereira, R., Couto, M., Ribeiro, F., Rua, R., Cunha, J., Fernandes, J. P., & Saraiva, J. (2021). Ranking programming languages by energy efficiency. Science of Computer Programming, 205, 102609. https://doi.org/https://doi.org/10.1016/j.scico.2021. 102609Precision Medicine Initiative (PMI) Working Group. (2015). The precision medicine initia- tive cohort program – building a research foundation for 21st century medicine (tech.rep.). http://www.nih.gov/precisionmedicineRavindran, P., & Gupta, A. (2015). Image processing for optical mapping. Gigascience, 4 (1), 1–8. https://doi.org/10.1186/s13742-015-0096-zReisner, W., Larsen, N. B., Silahtaroglu, A., Kristensen, A., Tommerup, N., Tegenfeldt, J. O., & Flyvbjerg, H. (2010). Single-molecule denaturation mapping of DNA in nanofluidic channels. Proceedings of the National Academy of Sciences, 107 (30), 13294–13299. https://doi.org/10.1073/pnas.1007081107Roy, A., Diao, Y., Evani, U., Abhyankar, A., Howarth, C., Le Priol, R., & Bloom, T. (2017). Massively Parallel Processing of Whole Genome Sequence Data, In Proc. 2017 acm int. conf. manag. data - sigmod ’17. https://doi.org/10.1145/3035918.3064048Rye, H. S., Yue, S., Wemmer, D. E., Quesada, M. A., Haugland, R. P., Mathies, R. A., & Glazer, A. N. (1992). Stable fluorescent complexes of double-stranded DNA with bis-intercalating asymmetric cyanine dyes: Properties and applications. Nucleic Acids Research, 20 (11), 2803–2812.Schwartz, D., Li, X., Hernandez, L., Ramnarain, S., Huff, E., & Wang, Y. (1993). Ordered restriction maps of Saccharomyces cerevisiae chromosomes constructed by optical mapping. Science 262 (5130), 110–114. https://doi.org/10.1126/science. 8211116Shapiro, H. (2004). Excitation and emission spectra of common dyes. Current Protocols in Cytometry, Chapter 1, Unit 1.19. https://doi.org/10.1002/0471142956.cy0119s26Shiguo, Z., Herscheleb, J., & Schwartz, D. C. (2007). A single molecule system for whole genome analysis., In New high throughput technol. dna seq. genomics.Shit, S., Paetzold, J. C., Sekuboyina, A., Zhylka, A., Ezhov, I., Unger, A., Pluim, J. P. W., Tetteh, G., & Menze, B. H. (2020). clDice – a Topology-Preserving Loss Function for Tubular Structure Segmentation, arXiv 2003.07311, 1–23. http://arxiv.org/abs/ 2003.07311Spielmann, H. P., Wemmer, D. E., & Jacobsen, J. P. (1995). Solution structure of a DNA complex with the fluorescent bis-intercalator TOTO determined by NMR spectroscopy. Biochemistry, 34 (27), 8542–8553.Tang, H., Lyons, E., & Town, C. D. (2015). Optical mapping in plant comparative genomics. Gigascience, 4 (1), 1–6. https://doi.org/10.1186/s13742-015-0044-yTeague, B., Waterman, M. S., Goldstein, S., Potamousis, K., Zhou, S., Reslewic, S., Sarkar, D., Valouev, A., Churas, C., Kidd, J. M., Kohn, S., Runnheim, R., Lamers, C., Forrest, D., Newton, M. A., Eichler, E. E., Kent-First, M., Surti, U., Livny, M., & Schwartz, D. C. (2010). High-resolution human genome structure by single-molecule analysis. Proc. Natl. Acad. Sci., 107 (24), 10848–10853. https://doi.org/10.1073/ pnas.0914638107Valouev, A., Schwartz, D. C., Zhou, S., & Waterman, M. S. (2006). An algorithm for assembly of ordered restriction maps from single DNA molecules. Proc. Natl. Acad. Sci., 103 (43), 15770–15775. https://doi.org/10.1073/pnas.0604040103Valouev, A., Li, L., Liu, Y.-C., Schwartz, D. C., Yang, Y., Zhang, Y., & Waterman, M. S. (2006). Alignment of Optical Maps. J. Comput. Biol., 13 (2), 442–462. https://doi. org/10.1089/cmb.2006.13.442Valouev, A., Zhang, Y., Schwartz, D. C., & Waterman, M. S. (2006). Refinement of optical map assemblies. Bioinformatics, 22 (10), 1217–1224. https://doi.org/10.1093/ bioinformatics/btl063Van der Walt, S., Sch ̈onberger, J. L., Nunez-Iglesias, J., Boulogne, F., Warner, J. D., Yager, N., Gouillart, E., & Yu, T. (2014). Scikit-image: Image processing in python. PeerJ, 2, e453.Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., . . . SciPy 1.0 Contributors. (2020). SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17, 261–272. https://doi.org/ 10.1038/s41592-019-0686-2Voigtl ̈ander, B. (2015). Data Representation and Image Processing (P. Avouris, B. Bhushan, D. Bimberg, H. Sakaki, K. von Klitzing, & R. Wiesendanger, Eds.; 1st ed.). In P. Avouris, B. Bhushan, D. Bimberg, H. Sakaki, K. von Klitzing, & R. Wiesendanger (Eds.), Scanning probe microsc. at. force microsc. scanning tunneling microsc. (1st ed.). Berlin, Heidelberg, Springer-Verlag GmbH Berlin Heidelberg. https://doi.org/10.1016/B978-0-12-814182-3.00005-5Zhou, S., & Schwartz, D. C. (2004). The Optical Mapping of Microbial Genomes. ASM News, 70 (7), 323–330.InvestigadoresLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83214/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1221966785.2022.pdf1221966785.2022.pdfTesis de Maestría en Ingeniería - Ingeniería de Sistemasapplication/pdf5903399https://repositorio.unal.edu.co/bitstream/unal/83214/2/1221966785.2022.pdfd3c070ea4829a531925f96d697bddf62MD52unal/83214oai:repositorio.unal.edu.co:unal/832142023-01-31 11:10:51.343Repositorio Institucional Universidad Nacional de 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A computational methodology for the generation of genomic maps from fluoroscanning images

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