DomSVR: Domain boundary prediction with support vector regression from sequence information alone

Publication Type:
Journal Article
Citation:
Amino Acids, 2010, 39 (3), pp. 713 - 726
Issue Date:
2010-08-01
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Protein domains are structural and fundamental functional units of proteins. The information of protein domain boundaries is helpful in understanding the evolution, structures and functions of proteins, and also plays an important role in protein classification. In this paper, we propose a support vector regression-based method to address the problem of protein domain boundary identification based on novel input profiles extracted from AA-index database. As a result, our method achieves an average sensitivity of ∼36.5% and an average specificity of ∼ 81% for multi-domain protein chains, which is overall better than the performance of published approaches to identify domain boundary. As our method used sequence information alone, our method is simpler and faster.© Springer-Verlag 2010.
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