Metabolic Flux Estimation-A Self-Adaptive Evolutionary Algorithm with Singular Value Decomposition
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An Introduction to Metabolic Networks and Their Structural Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Identification of gene regulatory pathways: a regularization method
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Analyzing metabolite measurements for automated prediction of underlying biological mechanisms
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
Predicting Metabolic Fluxes Using Gene Expression Differences As Constraints
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Genetic/bio design automation for (re-)engineering biological systems
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Decomposing Biochemical Networks Into Elementary Flux Modes Using Graph Traversal
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
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Motivation: Genome scale analysis of the metabolic network of a microorganism is a major challenge in bioinformatics. The combinatorial explosion, which occurs during the construction of elementary fluxes (non-redundant pathways) requires sophisticated and efficient algorithms to tackle the problem. Results: Mathematically, the calculation of elementary fluxes amounts to characterizing the space of solutions to a mixed system of linear equalities, given by the stoichiometry matrix, and linear inequalities, arising from the irreversibility of some or all of the reactions in the network. Previous approaches to this problem have iteratively solved for the equalities while satisfying the inequalities throughout the process. In an extension of previous work, here we consider the complementary approach and derive an algorithm which satisfies the inequalities one by one while staying in the space of solution of the equality constraints. Benchmarks on different subnetworks of the central carbon metabolism of Escherichia coli show that this new approach yields a significant reduction in the execution time of the calculation. This reduction arises since the odds that an intermediate elementary flux already fulfills an additional inequality are larger than when having to satisfy an additional equality constraint. Availability: The code is available upon request. Supplementary information: Pseudo code and a Mathematica implementation of the algorithm is on the OUP server. Contact:robert.urbanczik@pki.unibe.ch; clemens.wagner@pki.unibe.ch