Improving metabolic flux estimation via evolutionary optimization for convex solution space | Zendy

Jiusheng Chen | Zendy; Haoran Zheng | Zendy; Haiyan Liu | Zendy; Niu Junqing | Zendy; Jianping Liu | Zendy; Tie Shen | Zendy; Bin Rui | Zendy; Yunyu Shi | Zendy

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Improving metabolic flux estimation via evolutionary optimization for convex solution space

Author(s) -

Jiusheng Chen,

Haoran Zheng,

Haiyan Liu,

Niu Junqing,

Jianping Liu,

Tie Shen,

Bin Rui,

Yunyu Shi

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm050

Subject(s) - regular polygon , mathematical optimization , space (punctuation) , convex optimization , flux (metallurgy) , computer science , estimation , mathematics , materials science , geometry , economics , management , metallurgy , operating system

Flux estimation by using (13) C-labeling pattern information of metabolites is currently the only method that can give accurate, detailed quantification of all intracellular fluxes in the central metabolism of a microorganism. In essence, it corresponds to a constrained optimization problem which minimizes a weighted distance between measured and simulated results. Characteristics, such as existence of multiple local minima, non-linear and non-differentiable make this problem a special difficulty.

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