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A Data Fusion Approach in Protein Homology Detection

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3 Author(s)
Polatkan, A.C. ; Wilhelm-Schickard-Inst., Univ. Tubingen, Tubingen ; Ogul, H. ; Sever, H.

The discriminative framework for protein remote homology detection based on support vector machines (SVMs) is reconstructed by the fusion of sequence based features. In this respect, n-peptide compositions are partitioned and fed into separate SVMs. The SVM outputs are evaluated with different techniques and tested to discern their ability for SCOP protein super family classification on a common benchmarking set. It reveals that the fusion approach leads to an improvement in prediction accuracy with a remarkable gain on computer memory usage.

Published in:

Biocomputation, Bioinformatics, and Biomedical Technologies, 2008. BIOTECHNO '08. International Conference on

Date of Conference:

June 29 2008-July 5 2008