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BioMed Research InternationalVolume 2013 2013, Article ID 798743, 7 pages

Research Article

School of Materials Science and Engineering, Shanghai University, 149 Yan-Chang Road, Shanghai 200072, China

Department of Chemistry, College of Sciences, Shanghai University, 99 Shang-Da Road, Shanghai 200444, China

Department of Neurosurgery, Changhai Hospital, Second Military Medical University, 168 Chang-Hai Road, Shanghai 200433, China

Received 29 March 2013; Revised 10 May 2013; Accepted 28 May 2013

Academic Editor: Yudong Cai

Copyright © 2013 Tianhong Gu 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

The second development program developed in this work was introduced to obtain physicochemical properties of DPP-IV inhibitors. Based on the computation of molecular descriptors, a two-stage feature selection method called mRMR-BFS minimum redundancy maximum relevance-backward feature selection was adopted. Then, the support vector regression SVR was used in the establishment of the model to map DPP-IV inhibitors to their corresponding inhibitory activity possible. The squared correlation coefficient for the training set of LOOCV and the test set are 0.815 and 0.884, respectively. An online server for predicting inhibitory activity pIC50 of the DPP-IV inhibitors as described in this paper has been given in the introduction.





Autor: Tianhong Gu, Xiaoyan Yang, Minjie Li, Milin Wu, Qiang Su, Wencong Lu, and Yuhui Zhang

Fuente: https://www.hindawi.com/



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