Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework

Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework

Summary: Discovery of potential drugs requires rapid and precise identification of drug targets. Although traditional experimental methodologies can accurately identify drug targets, they are time-consuming and inappropriate for high-throughput screening. Computational approaches based on machine le...

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Bibliographic Details
Main Authors: Phasit Charoenkwan, Nalini Schaduangrat, Pietro Lio’, Mohammad Ali Moni, Watshara Shoombuatong, Balachandran Manavalan
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:iScience
Subjects:
Artificial intelligence
Artificial intelligence applications
Computational chemistry
Drugs
Online Access:http://www.sciencedirect.com/science/article/pii/S2589004222011555

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http://www.sciencedirect.com/science/article/pii/S2589004222011555

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