Hybrid optimization for 13C metabolic flux analysis using systems parametrized by compactification.

ABSTRACT:

Background

The importance and power of isotope-based metabolic flux analysis and its contribution to understanding the metabolic network is increasingly recognized. Its application is, however, still limited partly due to computational inefficiency. 13C metabolic flux analysis aims to compute in vivo metabolic fluxes in terms of metabolite balancing extended by carbon isotopomer balances and involves a nonlinear least-squares problem. To solve the problem more efficiently, improved numerical optimization techniques are necessary.

Results

For flux computation, we developed a gradient-based hybrid optimization algorithm. Here, independent flux variables were compactified into [0, 1)-ranged variables using a single transformation rule. The compactified parameters could be discr

SUBMITTER: Yang TH 

PROVIDER: S-EPMC2333969 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature