A Machine Learning Approach for Drug‐target Interaction Prediction using Wrapper Feature Selection and Class Balancing-Reference-Cited by-同舟云学术

A Machine Learning Approach for Drug‐target Interaction Prediction using Wrapper Feature Selection and Class Balancing

Published:2020-02-11 Issue:5 Volume:39 Page:1900062
ISSN:1868-1743
Container-title:Molecular Informatics
language:en
Short-container-title:Mol. Inf.

Author:

Redkar Shweta¹,Mondal Sukanta²,Joseph Alex³,Hareesha K. S.¹

Affiliation:

1. Department of Computer Applications, Manipal Institute of TechnologyManipal Academy of Higher Education 576104 Manipal Karnataka India

2. Department of Biological SciencesBirla Institute of Technology and Science-Pilani, K.K.Birla Goa Campus 403726 Zuarinagar Goa -India

3. Department of Pharmaceutical ChemistryManipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education 576104 Manipal Karnataka India

Publisher

Wiley

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,Molecular Medicine,Structural Biology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/minf.201900062

Reference50 articles.

1. Target selection in drug discovery

2. Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods

3. The role of ligand efficiency metrics in drug discovery

4. Binding mechanism of coronavirus main proteinase with ligands and its implication to drug design against SARS

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