关键词: 支持向量机, 快速傅里叶变换, 疏水性, 平均极性, 溶剂化自由能

Abstract: Membrane transport protein plays an important role in living cells.Currently，there are several methods to predict the membrane transport protein.However，there is limited number of published method to discriminate membrane transport proteins based on their functions.To approach this problem，a support vector machine based on fast Fourier transform is used to discriminate channels/pores，electrochemical potential-driven transporters and primary active transporters.Amino acid occurrence and modified Kyte-Doolittle hydrophobic scales，Ponnuswamy hydrophobic scales，mean polarity and solvation free energy，which are changed by fast Fourier transform，are used as support vector machine input vector.This method discriminates three transporters in transport classification database with the five-fold cross validation accuracy of 72.1% in a data set of 1718 membrane proteins.A preliminary literature-based validation had cross-validation accuracy 68.1%.This study suggests that the method can achieve a better accuracy and classify the transport into channels/pores，electrochemical and active transporters effectively.

Key words: Support Vector Machine（SVM）, Fast Fourier Transform（FFT）, hydrophobic scales, mean polarity, solvation free energy