title: Prediction of subcellular localization of apoptosis protein using Chou's pseudo amino acid composition.
abstract: Apoptosis proteins play an essential role in regulating a balance between cell proliferation and death. The successful prediction of subcellular localization of apoptosis proteins directly from primary sequence is much benefited to understand programmed cell death and drug discovery. In this paper, by use of Chou's pseudo amino acid composition (PseAAC), a total of 317 apoptosis proteins are predicted by support vector machine (SVM). The jackknife cross-validation is applied to test predictive capability of proposed method. The predictive results show that overall prediction accuracy is 91.1% which is higher than previous methods. Furthermore, another dataset containing 98 apoptosis proteins is examined by proposed method. The overall predicted successful rate is 92.9%.
authors.affiliation: Center for Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China. hlin@uestc.edu.cn
authors.forename: Hao
authors.initials: H
authors.lastname: Lin
authors.forename: Hao
authors.initials: H
authors.lastname: Wang
authors.forename: Hui
authors.initials: H
authors.lastname: Ding
authors.forename: Ying-Li
authors.initials: YL
authors.lastname: Chen
authors.forename: Qian-Zhong
authors.initials: QZ
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D017209:Apoptosis / Q000502:physiology*; D051017:Apoptosis Regulatory Proteins / Q000032:analysis* / Q000378:metabolism*; D030562:Databases, Protein; D006801:Humans; D008954:Models, Biological; D013347:Subcellular Fractions / Q000378:metabolism*
chemical_list: D000596:Amino Acids; D051017:Apoptosis Regulatory Proteins