Using feature selection technique for drug-target interaction networks prediction.

W Yu, Z Jiang, J Wang, R Tao
Author Information
  1. W Yu: Department of Computer Science & Technology, East China Normal University, Shanghai, 200241, PR China.

Abstract

Elucidating the interaction relationship between target proteins and all drugs is critical for the discovery of new drug targets. However, it is a big challenge to integrate and optimize different feature information into one single "knowledge view" for drug-target interaction prediction. In this article, a feature selection method was proposed to rank the original feature sets. Then, an improved bipartite learning graph method was used to predict four types of drug-target datasets based on the optimized feature subsets. The cross-validation results demonstrate that the proposed method can provide superior performance than previous method on four classes of drug target families.

MeSH Term

Binding Sites
Computational Biology
Computer Simulation
Drug Delivery Systems
Humans
Models, Biological
Pharmaceutical Preparations

Chemicals

Pharmaceutical Preparations

Word Cloud

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