Developing an SVM classifier for extended ES protein structure prediction
Piotr Fabian, Katarzyna Stąpor
DOI: http://dx.doi.org/10.15439/2017F322
Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 169–172 (2017)
Abstract. This article presents a new SVM classifier for the prediction of the extended early-stage (ES) protein structures. The classifier is based on physicochemical features and position-specific scoring matrix (PSSM). Experiments have shown that prediction results for specific classes are significantly better than those already obtained.
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