Predicting drug-target interactions using machine learning with improved data balancing and feature engineering

Predicting drug-target interactions using machine learning with improved data balancing and feature engineering

Abstract Drug-Target Interaction (DTI) prediction is a vital task in drug discovery, yet it faces significant challenges such as data imbalance and the complexity of biochemical representations. This study makes several contributions to address these issues, introducing a novel hybrid framework that...

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Bibliographic Details
Main Authors: Md. Alamin Talukder, Mohsin Kazi, Ammar Alazab
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Reports
Subjects:
Drug-Target interaction
Generative adversarial networks
Machine learning
Random forest classifier
Data imbalance
Computational drug discovery
Online Access:https://doi.org/10.1038/s41598-025-03932-6
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