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Prediction of amphipathic helices in transmembrane proteins by using ensembled classifier


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Prediction of amphipathic helices in transmembrane proteins by using ensembled classifier
Gao Faqi13Yu Dongjun2Shen Hongbin13
1.Institute of Image Processing and Pattern Recognition,Shanghai Jiao Tong University,Shanghai 200240,China; 2.School of Computer Science and Engineering,Nanjing University of Science and Technology, Nanjing 210094,China; 3.Key Laboratory of System Control and Information Processing, Ministry of Education of China,Shanghai 200240,China
transmembrane protein amphipathic helices position specific scoring matrix hydrophobic moment classifier ensemble
In order to improve the prediction accuracy of amphipathic helices(AHs),this paper develops a novel helix periodicity(HP)feature based on the position specific scoring matrix(PSSM),protein secondary structure and hydrophobic moment.MemBrain predictor is utilized to cut off the transmembrane segments; under-sampling and classifier ensemble are applied to cope with class imbalance.This paper implementes an ensembled support vector machine(SVM)classifier for performing AHs prediction.To objectively evaluate the prediction performance of AHs,a relative large benchmark data set regarding AHs prediction is constructed.Rigorous experimental tests demonstrate that the proposed method outperforms the existing AHs predictors on benchmark dataset.


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Last Update: 2016-06-30