Inference of Gene Networks from Microarray Data through a Phenomic Approach

dc.contributor.authorD'Souza, R.G.L.
dc.contributor.authorChandra Sekaran, K.C.
dc.contributor.authorKandasamy, A.
dc.date.accessioned2026-02-06T06:40:42Z
dc.date.issued2010
dc.description.abstractThe reconstruction of gene networks is crucial to the understanding of cellular processes which are studied in Systems Biology. The success of computational methods of drug discovery and disease diagnosis is dependent upon our understanding of the biological basis of the interaction networks between the genes. Better modelling of biological processes and powerful evolutionary methods are proving to be a key factor in the solution of such problems. However, most of these methods are based on processing of genotypic information. We present an evolutionary algorithm for inferring gene networks from expression data using phenotypic interactions. The benefit of this is that we avoid the need for an explicit objective function in the optimization process. In order to realize this, we have implemented a method called as the Phenomic algorithm and validated it for stability and accuracy in the reconstruction of gene networks. © Springer-Verlag Berlin Heidelberg 2010.
dc.identifier.citationCommunications in Computer and Information Science, 2010, Vol.101, , p. 83-89
dc.identifier.issn18650929
dc.identifier.urihttps://doi.org/10.1007/978-3-642-15766-0_13
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/33106
dc.subjectFitness function
dc.subjectGene networks
dc.subjectGenetic algorithms
dc.subjectMicroarray data analysis
dc.subjectPhenomic algorithms
dc.titleInference of Gene Networks from Microarray Data through a Phenomic Approach

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