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BioMed Research International
Volume 2017, Article ID 3267325, 4 pages
https://doi.org/10.1155/2017/3267325
Research Article

Predicting Presynaptic and Postsynaptic Neurotoxins by Developing Feature Selection Technique

1Department of Pathophysiology, Southwest Medical University, Luzhou 646000, China
2Department of Anesthesiology, The Affiliated Traditional Chinese Medical Hospital of Southwest Medical University, Luzhou 646000, China

Correspondence should be addressed to Hua Tang; moc.nuyila@112177auhgnat and Ping Zou; moc.361@gnipuozyl

Received 17 November 2016; Accepted 18 December 2016; Published 12 February 2017

Academic Editor: Ren-Zhi Cao

Copyright © 2017 Hua Tang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Presynaptic and postsynaptic neurotoxins are proteins which act at the presynaptic and postsynaptic membrane. Correctly predicting presynaptic and postsynaptic neurotoxins will provide important clues for drug-target discovery and drug design. In this study, we developed a theoretical method to discriminate presynaptic neurotoxins from postsynaptic neurotoxins. A strict and objective benchmark dataset was constructed to train and test our proposed model. The dipeptide composition was used to formulate neurotoxin samples. The analysis of variance (ANOVA) was proposed to find out the optimal feature set which can produce the maximum accuracy. In the jackknife cross-validation test, the overall accuracy of 94.9% was achieved. We believe that the proposed model will provide important information to study neurotoxins.