Rank-based interolog mapping for predicting proteinprotein interactions between genomes
As rapidly increasing number of sequenced genomes,the methods for predicting protein-protein interactions (PPIs) from one organism to another is becoming important.Best-match and generalized interolog mapping methods have been proposed for predicting (PPIs).However,best-match mapping method suffers from low coverage of the total interactome,because of using only best matches.Generalized interolog mapping method may predict unreliable interologs at a certain similarity cutoff,because of the homologs differed in subcellular compartment,biological process,or function from the query protein.Here,we propose a new rank-based interolog mapping method,which uses the pairs of proteins with high sequence similarity (E-value<10-10) and ranked by BLASTP Evalue in all possible homologs to predict interologs.First,we evaluated rank-based interolog mapping on predicting the PPIs in yeast.The accuracy at selecting top 5 and top 10 homologs are 0.17,and 0.12,respectively,and our method outperformed generalized interolog mapping method (accuracy=0.04) with the joint E-value<10-70.Furthermore,our method was used to predict PPIs in four organisms,including worm,fly,mouse,and human.In addition,we used Gene Ontology (GO) terms to analyzed PPIs,which reflect cellular component,biological process,and molecular function,inferred by rank-based mapping method.Our rank-based mapping method can predict more reliable interactions under a given percentage of false positives than the best-match and generalized interolog mapping methods.We believe that the rank-based mapping method is useful method for predicting PPIs in a genome-wide scale.
Rank-based strategy interolog mapping
Yu-Shu Lo Chun-Chen Chen Kai-Cheng Hsu Jinn-Moon Yang
Institute of Bioinformaticsand Systems Biology,National Chiao TungHsinchu, Taiwan
国际会议
7th International Conference on Systems Biology(第7届计算系统生物学国际研讨会)(ISB2013)
安徽黄山
英文
55-62
2013-08-22（万方平台首次上网日期，不代表论文的发表时间）