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Scientifica - Volume 2016 2016, Article ID 8309253, 10 pages -

Research Article

School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350108, China

School of Computer Science and Technology, Tianjin University, Tianjin 300350, China

School of Information Science and Technology, Xiamen University, Xiamen, Fujian 361005, China

State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China

Received 26 May 2016; Revised 26 June 2016; Accepted 30 June 2016

Academic Editor: Wei Chen

Copyright © 2016 Zhijun Liao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

G protein-coupled receptors GPCRs are the largest receptor superfamily. In this paper, we try to employ physical-chemical properties, which come from SVM-Prot, to represent GPCR. Random Forest was utilized as classifier for distinguishing them from other protein sequences. MEME suite was used to detect the most significant 10 conserved motifs of human GPCRs. In the testing datasets, the average accuracy was 91.61%, and the average AUC was 0.9282. MEME discovery analysis showed that many motifs aggregated in the seven hydrophobic helices transmembrane regions adapt to the characteristic of GPCRs. All of the above indicate that our machine-learning method can successfully distinguish GPCRs from non-GPCRs.





Author: Zhijun Liao, Ying Ju, and Quan Zou

Source: https://www.hindawi.com/



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