Mining drug-target interactions from biomedical literature using chemical and gene descriptions-based ensemble transformer model.

ABSTRACT:

Motivation

Drug-target interactions (DTIs) play a pivotal role in drug discovery, as it aims to identify potential drug targets and elucidate their mechanism of action. In recent years, the application of natural language processing (NLP), particularly when combined with pre-trained language models, has gained considerable momentum in the biomedical domain, with the potential to mine vast amounts of texts to facilitate the efficient extraction of DTIs from the literature.

Results

In this article, we approach the task of DTIs as an entity-relationship extraction problem, utilizing different pre-trained transformer language models, such as BERT, to extract DTIs. Our results indicate that an ensemble approach, by combining gene descriptions from the Entrez Gene database with ch

SUBMITTER: Aldahdooh J 

PROVIDER: S-EPMC11293871 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature