Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure

Description

Biclustering is an unsupervised machine learning technique that simultaneously clusters genes and conditions in gene expression data. Gene Ontology (GO) is usually used in this context to validate the biological relevance of the results. However, although the integration of biological information from different sources is one of the research directions in Bioinformatics, GO is not used in biclustering as an input data. A scatter search-based algorithm that integrates GO information during the biclustering search process is presented in this paper. SimUI is a GO semantic similarity measure that defines a distance between two genes. The algorithm optimizes a fitness function that uses SimUI to integrate the biological information stored in GO. Experimental results analyze the effect of integration of the biological information through this measure. A SimUI fitness function configuration is experimentally studied in a scatter search-based biclustering algorithm

Abstract

Ministerio de Ciencia e Innovación TIN2011-28956-C02-02

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Ministerio de Ciencia e Innovación TIN2014-55894-C2-R

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Junta de Andalucía P12-TIC-1728

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Universidad Pablo de Olavide APPB813097

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