title: Using protein-protein interaction network information to predict the subcellular locations of proteins in budding yeast.
abstract: The information of protein subcellular localization is vitally important for in-depth understanding the intricate pathways that regulate biological processes at the cellular level. With the rapidly increasing number of newly found protein sequence in the Post-Genomic Age, many automated methods have been developed attempting to help annotate their subcellular locations in a timely manner. However, very few of them were developed using the protein-protein interaction (PPI) network information. In this paper, we have introduced a new concept called "tethering potential" by which the PPI information can be effectively fused into the formulation for protein samples. Based on such a network frame, a new predictor called Yeast-PLoc has been developed for identifying budding yeast proteins among their 19 subcellular location sites. Meanwhile, a purely sequence-based approach, called the "hybrid-property" method, is integrated into Yeast-PLoc as a fall-back to deal with those proteins without sufficient PPI information. The overall success rate by the jackknife test on the 4,683 yeast proteins in the training dataset was 70.25%. Furthermore, it was shown that the success rate by Yeast- PLoc on an independent dataset was remarkably higher than those by some other existing predictors, indicating that the current approach by incorporating the PPI information is quite promising. As a user-friendly web-server, Yeast-PLoc is freely accessible at http://yeastloc.biosino.org/.
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai, China.
authors.forename: Le-Le
authors.initials: LL
authors.lastname: Hu
authors.forename: Kai-Yan
authors.initials: KY
authors.lastname: Feng
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D030562:Databases, Protein; D042541:Intracellular Space / Q000378:metabolism; D015233:Models, Statistical; D060066:Protein Interaction Maps; D020543:Proteome / Q000378:metabolism; D040901:Proteomics / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000166:cytology / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000378:metabolism*; D012984:Software; D013347:Subcellular Fractions / Q000737:chemistry / Q000378:metabolism
chemical_list: D020543:Proteome; D029701:Saccharomyces cerevisiae Proteins