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http://dx.doi.org/10.5808/GI.2009.7.3.141

A New Approach to Find Orthologous Proteins Using Sequence and Protein-Protein Interaction Similarity  

Kim, Min-Kyung (Department of Bioinformatics and CAMDRC, Soongsil University)
Seol, Young-Joo (Research Planning & Information Div., National Institute of Agricultural Biotechnology, RDA)
Park, Hyun-Seok (Department of Computer Science, Ewha Womans University)
Jang, Seung-Hwan (Department of Bioinformatics and CAMDRC, Soongsil University)
Shin, Hang-Cheol (Department of Bioinformatics and CAMDRC, Soongsil University)
Cho, Kwang-Hwi (Department of Bioinformatics and CAMDRC, Soongsil University)
Publication Information
Genomics & Informatics / v.7, no.3, 2009 , pp. 141-147 More about this Journal
Abstract
Developed proteome-scale ortholog and paralog prediction methods are mainly based on sequence similarity. However, it is known that even the closest BLAST hit often does not mean the closest neighbor. For this reason, we added conserved interaction information to find orthologs. We propose a genome-scale, automated ortholog prediction method, named OrthoInterBlast. The method is based on both sequence and interaction similarity. When we applied this method to fly and yeast, 17% of the ortholog candidates were different compared with the results of Inparanoid. By adding protein-protein interaction information, proteins that have low sequence similarity still can be selected as orthologs, which can not be easily detected by sequence homology alone.
Keywords
interolog; ortholog; protein-protein interaction;
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