A discriminative method for remote homology detection based on n-peptide compositions with reduced amino acid alphabets

Date

2007-01-01

Author

OĞUL, Hasan
Mumcuoğlu, Ünal Erkan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this study, n-peptide compositions are utilized for protein vectorization over a discriminative remote homology detection framework based on support vector machines (SVMs). The size of amino acid alphabet is gradually reduced for increasing values of n to make the method to conform with the memory resources in conventional workstations. A hash structure is implemented for accelerated search of n-peptides. The method is tested to see its ability to classify proteins into families on a subset of SCOP family database and compared against many of the existing homology detection methods including the most popular generative methods; SAM-98 and PSI-BLAST and the recent SVM methods; SVM-Fisher, SVM-BLAST and SVM-Pairwise. The results have demonstrated that the new method significantly outperforms SVM-Fisher, SVM-BLAST, SAM-98 and PSI-BLAST, while achieving a comparable accuracy with SVM-Pairwise. In terms of efficiency, it performs much better than SVM-Pairwise. It is shown that the information of n-peptide compositions with reduced amino acid alphabets provides an accurate and efficient means of protein vectorization for SVM-based sequence classification. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Subject Keywords

Remote homology, Support vector machine, Protein vectorization, Composition, Reduced alphabet

URI

https://hdl.handle.net/11511/30345

Journal

BIOSYSTEMS

DOI

https://doi.org/10.1016/j.biosystems.2006.03.006

Collections

Graduate School of Informatics, Article

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Citation Formats

H. OĞUL and Ü. E. Mumcuoğlu, “A discriminative method for remote homology detection based on n-peptide compositions with reduced amino acid alphabets,” BIOSYSTEMS, pp. 75–81, 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30345.