title: Predicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier.
abstract: Apoptosis proteins play a key role in maintaining the stability of organism; the functions of apoptosis proteins are related to their subcellular locations which are used to understand the mechanism of programmed cell death. In this paper, we utilize GO annotation information of apoptosis proteins and their homologous proteins retrieved from GOA database to formulate feature vectors and then combine the distance weighted KNN classification algorithm with them to solve the data imbalance problem existing in CL317 data set to predict subcellular locations of apoptosis proteins. It is found that the number of homologous proteins can affect the overall prediction accuracy. Under the optimal number of homologous proteins, the overall prediction accuracy of our method on CL317 data set reaches 96.8% by Jackknife test. Compared with other existing methods, it shows that our proposed method is very effective and better than others for predicting subcellular localization of apoptosis proteins.
authors.affiliation: School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Wang
authors.affiliation: School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Li
authors.affiliation: School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
authors.forename: Qiuwen
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
authors.forename: Rong
authors.initials: R
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D051017:Apoptosis Regulatory Proteins / Q000378:metabolism*; D030562:Databases, Protein; D063990:Gene Ontology; D006801:Humans; D058977:Molecular Sequence Annotation / Q000379:methods; D017386:Sequence Homology, Amino Acid
chemical_list: D051017:Apoptosis Regulatory Proteins