title: Support vector machines for predicting apoptosis proteins types.
abstract: Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death, and their function is related to their types. According to the classification scheme by Zhou and Doctor (2003), the apoptosis proteins are categorized into the following four types: (1) cytoplasmic protein; (2) plasma membrane-bound protein; (3) mitochondrial inner and outer proteins; (4) other proteins. A powerful learning machine, the Support Vector Machine, is applied for predicting the type of a given apoptosis protein by incorporating the sqrt-amino acid composition effect. High success rates were obtained by the re-substitute test (98/98 = 100 %) and the jackknife test (89/98 = 90.8%).
authors.affiliation: School of Computer, Wuhan University, Hubei Province, PR China. caroline_hj@sohu.com
authors.forename: Jing
authors.initials: J
authors.lastname: Huang
authors.forename: Feng
authors.initials: F
authors.lastname: Shi
mesh_terms: D017209:Apoptosis; D011506:Proteins / Q000145:classification* / Q000502:physiology; D013347:Subcellular Fractions
chemical_list: D011506:Proteins