Current Challenges in Modeling Cellular Metabolism
Mathematical and computational models play an essential role in understanding the cellular metabolism. They are used as platforms to integrate current knowledge on a biological system and to systematically test and predict the effect of manipulations to such systems. The recent advances in genome se...
- Autores:
- Tipo de recurso:
- Book
- Fecha de publicación:
- 2016
- Institución:
- Universidad de Bogotá Jorge Tadeo Lozano
- Repositorio:
- Expeditio: repositorio UTadeo
- Idioma:
- eng
- OAI Identifier:
- oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/14256
- Acceso en línea:
- https://www.frontiersin.org/research-topics/2234/current-challenges-in-modeling-cellular-metabolism
http://hdl.handle.net/20.500.12010/14256
- Palabra clave:
- Biology
Science (General)
Biotechnology
General and civil engineering
Mathematical Models
Phenotype simulation
Cellular metabolism
Computational methods
Systems biology
Modeling formalisms
Metabolic Engineering
Metabolic Regulation
- Rights
- License
- Abierto (Texto Completo)
Summary: | Mathematical and computational models play an essential role in understanding the cellular metabolism. They are used as platforms to integrate current knowledge on a biological system and to systematically test and predict the effect of manipulations to such systems. The recent advances in genome sequencing techniques have facilitated the reconstruction of genome-scale metabolic networks for a wide variety of organisms from microbes to human cells. These models have been successfully used in multiple biotechnological applications. Despite these advancements, modeling cellular metabolism still presents many challenges. The aim of this Research Topic is not only to expose and consolidate the state-of-the-art in metabolic modeling approaches, but also to push this frontier beyond the current edge through the introduction of innovative solutions. The articles presented in this e-book address some of the main challenges in the field, including the integration of different modeling formalisms, the integration of heterogeneous data sources into metabolic models, explicit representation of other biological processes during phenotype simulation, and standardization efforts in the representation of metabolic models and simulation results. |
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