摘要
AcomputationalsystemforthepredictionandclassificationofhumanG-proteincoupledreceptors(GPCRs)hasbeendevelopedbasedonthesupportvectormachine(SVM)methodandproteinsequenceinformation.ThefeaturevectorsusedtodeveloptheSVMpredictionmodelsconsistofstatisticallysignificantfeaturesselectedfromsingleaminoacid,dipeptide,andtripeptidecompositionsofproteinsequences.Furthermore,thelengthdistributiondifferencebetweenGPCRsandnon-GPCRshasalsobeenexploitedtoimprovethepredictionperformance.ThetestingresultswithannotatedhumanproteinsequencesdemonstratethatthissystemcangetgoodperformanceforbothpredictionandclassificationofhumanGPCRs.
出版日期
2005年04月14日(中国期刊网平台首次上网日期,不代表论文的发表时间)