influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments | Zendy

Sergueï Sokol | Zendy; Pierre Millard | Zendy; JeanCharles Portais | Zendy

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influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments

Author(s) -

Sergueï Sokol,

Pierre Millard,

JeanCharles Portais

Publication year - 2011

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/btr716

Subject(s) - software , computer science , stability (learning theory) , algorithm , simulated annealing , convergence (economics) , flux (metallurgy) , labelling , software package , mathematical optimization , mathematics , machine learning , chemistry , organic chemistry , economics , programming language , economic growth , biochemistry

The problem of stationary metabolic flux analysis based on isotope labelling experiments first appeared in the early 1950s and was basically solved in early 2000s. Several algorithms and software packages are available for this problem. However, the generic stochastic algorithms (simulated annealing or evolution algorithms) currently used in these software require a lot of time to achieve acceptable precision. For deterministic algorithms, a common drawback is the lack of convergence stability for ill-conditioned systems or when started from a random point.

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