Engineering

Volume 5, Issue 10 (October 2013)

ISSN Print: 1947-3931   ISSN Online: 1947-394X

Google-based Impact Factor: 1.09  Citations  

Using Chou’s Pseudo Amino Acid Composition for Protein Remote Homology Detection

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DOI: 10.4236/eng.2013.510B032    3,419 Downloads   5,013 Views  Citations
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ABSTRACT

Protein remote homology detection is a key problem in bioinformatics. Currently, the discriminative methods, such as Support Vector Machine (SVM), can achieve the best performance. The most efficient approach to improve the performance of the SVM-based methods is to find a general protein representation method that is able to convert proteins with different lengths into fixed length vectors and captures the different properties of the proteins for the discrimination. The bottleneck of designing the protein representation method is that native proteins have different lengths. Motivated by the success of the pseudo amino acid composition (PseAAC) proposed by Chou, we applied this approach for protein remote homology detection. Some new indices derived from the amino acid index (AAIndex) database are incorporated into the PseAAC to improve the generalization ability of this method. Our experiments on a well-known benchmark show this method achieves superior or comparable performance with current state-of-the-art methods.

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Liu, B. and Wang, X. (2013) Using Chou’s Pseudo Amino Acid Composition for Protein Remote Homology Detection. Engineering, 5, 149-153. doi: 10.4236/eng.2013.510B032.

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