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Protein structural classification based on pseudo amino acid composition using SVM classifier

Paper ID Volume ID Publish Year Pages File Format Full-Text
5278 360 2013 11 PDF Available
Title
Protein structural classification based on pseudo amino acid composition using SVM classifier
Abstract

This paper deals with a structural classification by the aid of support vector machine (SVM) classifier. Amino acid composition (AAC) and pseudo amino acid composition (PseAA) features were applied with different variants. Additionally the feature reflecting the length of protein chain was taken into consideration. The SVM classifier was compared to minimal-length classifiers with respect to the AAC features. The best model of SVM classifier was chosen using grid method on the basis of cross-validation (CV) as criterion. The best model of SVM classifier is evaluated with respect to proper evaluation rates. The SCOP database and the ASTRAL tool were a source of non-homologous data to avoid the redundancy and to ensure a maximal amount of available data.

Keywords
Pseudo amino acid composition; Support vector machine; Minimal-distance methods; Protein structural class; SCOP database
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Protein structural classification based on pseudo amino acid composition using SVM classifier
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biocybernetics and Biomedical Engineering - Volume 33, Issue 2, 2013, Pages 77–87
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us