Submit Manuscript  

Article Details


Prediction of G-Protein-Coupled Receptor Classes in Low Homology Using Chous Pseudo Amino Acid Composition with Approximate Entropy and Hydrophobicity Patterns

[ Vol. 17 , Issue. 5 ]

Author(s):

Quan Gu, Yong-Sheng Ding and Tong-Liang Zhang   Pages 559 - 567 ( 9 )

Abstract:


We use approximate entropy and hydrophobicity patterns to predict G-protein-coupled receptors. Adaboost classifier is adopted as the prediction engine. A low homology dataset is used to validate the proposed method. Compared with the results reported, the successful rate is encouraging. The source code is written by Matlab.

Keywords:

G-protein-coupled receptors, low homology, pseudo amino acid, approximate entropy, hydrophobicity patterns, AdaBoost

Affiliation:

College of Information Sciences and Technology, Donghua University, Shanghai 201620, P.R. China.



Read Full-Text article