Reverse engineering genetic networks using evolutionary computation.

Nasimul Noman; Hitoshi Iba

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PubMed · 16901103

Reverse engineering genetic networks using evolutionary computation.

Nasimul Noman·Hitoshi Iba

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Abstract

This paper proposes an improved evolutionary method for constructing the underlying network structure and inferring effective kinetic parameters from the time series data of gene expression using decoupled S-system formalism. We employed Trigonometric Differential Evolution (TDE) as the optimization engine of our algorithm for capturing the dynamics in gene expression data. A more effective fitness function for attaining the sparse structure, which is the hallmark of biological networks, has been applied. Experiments on artificial genetic network show the power of the algorithm in constructing the network structure and predicting the regulatory parameters. The method is used to evaluate interactions between genes in the SOS signaling pathway in Escherichia coli using gene expression data.

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Algorithms Biological Evolution Computational Biology Escherichia coli Gene Expression Profiling Oligonucleotide Array Sequence Analysis Protein Engineering Journal Article

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Nasimul Noman, Hitoshi Iba. 2005. Reverse engineering genetic networks using evolutionary computation.. https://pubmed.ncbi.nlm.nih.gov/16901103/

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