title: Using search engine technology for protein function prediction.
abstract: Prediction of protein function is one of the most challenging problems in the post-genomic era. In this paper, we propose a novel algorithm Improved ProteinRank (IPR) for protein function prediction, which is based on the search engine technology and the preferential attachment criteria. In addition, an improved algorithm IPRW is developed from IPR to be used in the weighted protein?protein interaction (PPI) network. The proposed algorithms IPR and IPRW are applied to the PPI network of S.cerevisiae. The experimental results show that both IPR and IPRW outweigh the previous methods for the prediction of protein functions.
authors: College of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China. zychen@ysu.edu.cn
authors: Ziyang
authors: Z
authors: Chen
authors: Zhao
authors: Z
authors: Cai
authors: Min
authors: M
authors: Li
authors: Binbin
authors: B
authors: Liu
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D025941:Protein Interaction Mapping / Q000706:statistics & numerical data*; D011506:Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D040901:Proteomics / Q000706:statistics & numerical data; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D057386:Search Engine
chemical_list: D011506:Proteins; D029701:Saccharomyces cerevisiae Proteins