Metabolic modeling of microbial strains in silico

Markus W Covert; Christophe H Schilling; Iman Famili; Jeremy S Edwards; Igor I Goryanin; Evgeni Selkov; Bernhard O Palsson

doi:10.1016/S0968-0004(00)01754-0

Metabolic modeling of microbial strains in silico

Markus W Covert, Christophe H Schilling, Iman Famili, Jeremy S Edwards, Igor I Goryanin, Evgeni Selkov, Bernhard O Palsson

School of Informatics

Research output: Contribution to journal › Article › peer-review

Abstract

The large volume of genome-scale data that is being produced and made available in databases on the World Wide Web is demanding the development of integrated mathematical models of cellular processes. The analysis of reconstructed metabolic networks as systems leads to the development of an in silico or computer representation of collections of cellular metabolic constituents, their interactions and their integrated function as a whole. The use of quantitative analysis methods to generate testable hypotheses and drive experimentation at a whole-genome level signals the advent of a systemic modeling approach to cellular and molecular biology.

Original language	English
Pages (from-to)	179-186
Number of pages	8
Journal	Trends in biochemical sciences
Volume	26
Issue number	3
DOIs	https://doi.org/10.1016/S0968-0004(00)01754-0
Publication status	Published - 2001

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http://www.sciencedirect.com/science/article/pii/S0968000400017540

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AU - Schilling, Christophe H

AU - Famili, Iman

AU - Edwards, Jeremy S

AU - Goryanin, Igor I

AU - Selkov, Evgeni

AU - Palsson, Bernhard O

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AB - The large volume of genome-scale data that is being produced and made available in databases on the World Wide Web is demanding the development of integrated mathematical models of cellular processes. The analysis of reconstructed metabolic networks as systems leads to the development of an in silico or computer representation of collections of cellular metabolic constituents, their interactions and their integrated function as a whole. The use of quantitative analysis methods to generate testable hypotheses and drive experimentation at a whole-genome level signals the advent of a systemic modeling approach to cellular and molecular biology.

U2 - 10.1016/S0968-0004(00)01754-0

DO - 10.1016/S0968-0004(00)01754-0

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SP - 179

EP - 186

JO - Trends in biochemical sciences

JF - Trends in biochemical sciences

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ER -

Metabolic modeling of microbial strains in silico

Abstract

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