Classifying g-protein coupled receptors with hydropathy blocks and support vector machines

  • Authors:

  • Xing-Ming Zhao;De-Shuang Huang;Shiwu Zhang;Yiu-ming Cheung

  • Affiliations:

  • Institute of Intelligent Machines, CAS, Hefei, Anhui, China;Institute of Intelligent Machines, CAS, Hefei, Anhui, China;Department of Precision Machinery and Instrumentation, University of Science and Technology of China, Hefei, Anhui, China;Department of Computer Science, Hong Kong Baptist University, Hong Kong, China

  • Venue:
  • ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
  • Year:
  • 2006

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Abstract

This paper developes a new method for recognizing G-Protein Coupled Receptors (GPCRs) based on features generated from the hydropathy properties of the amino acid sequences. Using the hydropathy characteristics, namely hydropathy blocks, the protein sequences are converted into fixed-dimensional feature vectors. Subsequently, the Support Vector Machine (SVM) classifier is utilized to identify the GPCR proteins belonging to the same families or subfamilies. The experimental results on GPCR datasets show that the proteins belonging to the same family or subfamily can be identified using features generated based on the hydropathy blocks.