A novel hybrid GA/SVM system for protein sequences classification

作者：Zhao XM^*; Huang DS; Cheung YM; Wang HQ; Huang X

来源：INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING IDEAL 2004, PROCEEDINGS, SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 11-16, 2004.

A novel hybrid genetic algorithm(GA)/Support Vector Machine (SVM) system, which selects features from the protein sequences and trains the SVM classifier simultaneously using a multi-objective genetic algorithm, is proposed in this paper. The system is then applied to classify protein sequences obtained from the Protein Information Resource (PIR) protein database. Finally, experimental results over six protein superfamilies are reported, where it is shown that the proposed hybrid GA/SVM system outperforms BLAST and HMMer.

• 出版日期2004
• 单位中国科学院