Automatic orthologous-protein-clustering from multiple complete-genomes by the best reciprocal BLAST hits

Authors:
Sunshin Kim;Kwang Su Jung;Keun Ho Ryu
Affiliations:
Database/Bioinformatics Laboratory, Department of Computer Science, Chungbuk National University, Cheongju, South Korea;Database/Bioinformatics Laboratory, Department of Computer Science, Chungbuk National University, Cheongju, South Korea;Database/Bioinformatics Laboratory, Department of Computer Science, Chungbuk National University, Cheongju, South Korea
Venue:
BioDM'06 Proceedings of the 2006 international conference on Data Mining for Biomedical Applications
Year:
2006

Citing 1
Cited 1

Phylogenomic inference of protein molecular function: advances and challenges

Bioinformatics

Classification of Ligase Function Based on Multi-parametric Feature Extracted from Protein Sequence

ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II

Quantified Score

Hi-index	0.01

Visualization

Abstract

Though the number of completely sequenced genomes quickly grows in recent years, the methods to predict protein functions by homology from the genomes have not been used sufficiently. It has been a successful technique to construct an OPCs(Orthologous Protein Clusters) with the best reciprocal BLAST hits from multiple complete-genomes. But it takes time-consuming-processes to make the OPCs with manual work. We, here, propose an automatic method that clusters OPs(Orthologous Proteins) from multiple complete-genomes, which is, to be extended, based on INPARANOID which is an automatic program to detect OPs between two complete-genomes. We also prove all possible clustering mathematically.