Integration of expression data in genome-scale metabolic network reconstructions.

Abstract:

:With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of "omics" data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA), a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

journal_name

Front Physiol

journal_title

Frontiers in physiology

authors

Blazier AS,Papin JA

doi

10.3389/fphys.2012.00299

subject

Has Abstract

pub_date

2012-08-06 00:00:00

pages

299

issn

1664-042X

journal_volume

3

pub_type

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