Sammanfattning

Drug-target interactions (DTIs) are critical for drug repurposing and elucidation of drug mechanisms, and are manually curated by large databases, such as ChEMBL, BindingDB, DrugBank and DrugTargetCommons. However, the number of curated articles likely constitutes only a fraction of all the articles that contain experimentally determined DTIs. Finding such articles and extracting the experimental information is a challenging task, and there is a pressing need for systematic approaches to assist the curation of DTIs. To this end, we applied Bidirectional Encoder Representations from Transformers (BERT) to identify such articles. Because DTI data intimately depends on the type of assays used to generate it, we also aimed to incorporate functions to predict the assay format.
Originalspråkengelska
Artikelnummer245
TidskriftBMC Bioinformatics
Volym23
Nummer1
Antal sidor13
ISSN1471-2105
DOI
StatusPublicerad - 21 juni 2022
MoE-publikationstypA1 Tidskriftsartikel-refererad

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