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

Author(s): Quan Gu, Yong-Sheng Ding, Tong-Liang Zhang.

Journal Name: Protein & Peptide Letters

Volume 17 , Issue 5 , 2010

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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

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Article Details

VOLUME: 17
ISSUE: 5
Year: 2010
Page: [559 - 567]
Pages: 9
DOI: 10.2174/092986610791112693
Price: $58

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