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. 2010 Jun 1;26(12):i255–i260. doi: 10.1093/bioinformatics/btq183

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© The Author(s) 2010. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Fig. 4. — An example flux distribution predicted by IOMA following the knockout of talB (Transaldolase B). The network shows E.coli's glycolysis and PPP. Green (red) edges represent a measured increase (decrease) of flux between the wild-type and knockout strains. The letters F, M and I, represent predictions made by FBA, MOMA and IOMA, respectively, with green (red), representing a predicted increase (decrease) in flux. Predictions of no significant change in flux are not shown. As evident, IOMA correctly predicts the measured pattern of increased flux throughout glycolysis and decreased flux throughout the PPP pathways, with only two mismatches, while FBA and MOMA perform significantly worse.