Barlow Twins deep neural network for advanced 1D drug-target interaction prediction.

ABSTRACT: Accurate prediction of drug-target interactions is critical for advancing drug discovery. By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. In a novel approach, BarlowDTI, we utilise the powerful Barlow Twins architecture for feature-extraction while considering the structure of the target protein. Our method achieves state-of-the-art predictive performance against multiple established benchmarks using only one-dimensional input. The use of our hybrid approach of deep learning and gradient boosting machine as the underlying predictor ensures fast and efficient predictions without the need for substantial computational resources. We also propose the use of an influence method to investigate how the model reaches its decision based

SUBMITTER: Schuh MG 

PROVIDER: S-EPMC11800607 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature