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Published October 2015 | Published + Supplemental Material
Journal Article Open

Do genome-scale models need exact solvers or clearer standards?

Abstract

Constraint‐based analysis of genome‐scale models (GEMs) arose shortly after the first genome sequences became available. As numerous reviews of the field show, this approach and methodology has proven to be successful in studying a wide range of biological phenomena (McCloskey et al, 2013; Bordbar et al, 2014). However, efforts to expand the user base are impeded by hurdles in correctly formulating these problems to obtain numerical solutions. In particular, in a study entitled "An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models" (Chindelevitch et al, 2014), the authors apply an exact solver to 88 genome‐scale constraint‐based models of metabolism. The authors claim that COBRA calculations (Orth et al, 2010) are inconsistent with their results and that many published and actively used (Lee et al, 2007; McCloskey et al, 2013) genome‐scale models do support cellular growth in existing studies only because of numerical errors. They base these broad claims on two observations: (i) three reconstructions (iAF1260, iIT341, and iNJ661) compute feasibly in COBRA, but are infeasible when exact numerical algorithms are used by their software (entitled MONGOOSE); (ii) linear programs generated by MONGOOSE for iIT341 were submitted to the NEOS Server (a Web site that runs linear programs through various solvers) and gave inconsistent results. They further claim that a large percentage of these COBRA models are actually unable to produce biomass flux. Here, we demonstrate that the claims made by Chindelevitch et al (2014) stem from an incorrect parsing of models from files rather than actual problems with numerical error or COBRA computations.

Additional Information

© 2015 The Authors. Published under the terms of the CC BY 4.0 license. This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Article first published online: 14 OCT 2015. We thank Leonid Chindelevitch for extensive discussions and for sharing results obtained with the MONGOOSE platform for comparison with solutions obtained with COBRA software. Author contributions: AE wrote the code and assembled the models included in Dataset EV1. All of the authors contributed to the design, approach, and written manuscript. Subsequent authors are arranged alphabetically by last name.

Attached Files

Published - Ebrahim_et_al-2015-Molecular_Systems_Biology.pdf

Supplemental Material - inline-supplementary-material-1.xlsx

Supplemental Material - inline-supplementary-material-2.zip

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