Ranking through integration of protein-similarity for identification of cell-cyclic genes

Authors:
Sumeet Dua;Pradeep Chowriappa;Alan E. Alex
Affiliations:
Department of Computer Science, Louisiana Tech University, Ruston, LA 71272, USA.;Department of Computer Science, Louisiana Tech University, Ruston, LA 71272, USA.;Department of Computer Science, Louisiana Tech University, Ruston, LA 71272, USA
Venue:
International Journal of Bioinformatics Research and Applications
Year:
2010

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Abstract

Gene array experiments are progressively conducted. However, the biological functional interpretation has not kept pace with this rapid escalation. Functional genomics using data mining methods potentially offers precise, objective, and more reliable gene identification. Our work creates a gene-ranking scheme by integrating gene expression profile phase information with protein similarity to identify cell-cyclic genes. We present a unique schema to enable integration by employing QR-factorisation from the pair-wise similarity matrix formulation. Angular coefficients are derived and consequently employed for integrated gene ranking. Experimental results on an independent benchmark dataset signify the efficacy of the method.