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 crossvalidation results demonstrate that the proposed method can provide superior performance than previous method on four classes of drug target families.
Keywords: Drug-target interaction, feature selection method, improved bipartite learning graph method, Elucidating, target proteins, drug target families, biological macromolecules, pathological states, drug targets undetectably, algorithm
Current Medicinal Chemistry
Title: Using Feature Selection Technique for Drug-Target Interaction Networks Prediction
Volume: 18 Issue: 36
Author(s): W. Yu, Z. Jiang, J. Wang and R. Tao
Affiliation:
Keywords: Drug-target interaction, feature selection method, improved bipartite learning graph method, Elucidating, target proteins, drug target families, biological macromolecules, pathological states, drug targets undetectably, algorithm
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 crossvalidation results demonstrate that the proposed method can provide superior performance than previous method on four classes of drug target families.
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Cite this article as:
Yu W., Jiang Z., Wang J. and Tao R., Using Feature Selection Technique for Drug-Target Interaction Networks Prediction, Current Medicinal Chemistry 2011; 18 (36) . https://dx.doi.org/10.2174/092986711798347270
DOI https://dx.doi.org/10.2174/092986711798347270 |
Print ISSN 0929-8673 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-533X |
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