{"doi":"10.3233/shti231043","title":"Extracting Drug-Protein Relation from Literature Using Ensembles of Biomedical Transformers","abstract":"Automatic extraction of relations between drugs/chemicals and proteins from ever-growing biomedical literature is required to build up-to-date knowledge bases in biomedicine. To promote the development of automated methods, BioCreative-VII organized a shared task - the DrugProt track, to recognize drug-protein entity relations from PubMed abstracts. We participated in the shared task and leveraged deep learning-based transformer models pre-trained on biomedical data to build ensemble approaches to automatically extract drug-protein relation from biomedical literature. On the main corpora of 10,750 abstracts, our best system obtained an F1-score of 77.60% (ranked 4th among 30 participating teams), and on the large-scale corpus of 2.4M documents, our system achieved micro-averaged F1-score of 77.32% (ranked 2nd among 9 system submissions). This demonstrates the effectiveness of domain-specific transformer models and ensemble approaches for automatic relation extraction from biomedical literature.","journal":"Studies in health technology and informatics","year":2024,"id":493633,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9345,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1340078,"name":"Li Zhao","orcid":"0000-0001-5095-3377","position":1,"is_corresponding":false},{"id":413132,"name":"Wei Qiang","orcid":"0000-0002-0044-810X","position":2,"is_corresponding":false},{"id":606869,"name":"Jianfu Li","orcid":"0009-0004-9378-8462","position":3,"is_corresponding":false},{"id":282866,"name":"Liang‐Chin Huang","orcid":"0000-0001-5661-8940","position":4,"is_corresponding":false},{"id":1199064,"name":"Yan Hu","orcid":"0009-0008-2413-5918","position":5,"is_corresponding":false},{"id":1095353,"name":"Rongbin Li","orcid":"0000-0001-6246-5004","position":6,"is_corresponding":false},{"id":12654,"name":"W. Jim Zheng","orcid":"0000-0001-7411-6047","position":7,"is_corresponding":false},{"id":1325713,"name":"Hua Xu","orcid":"0000-0001-8470-5558","position":8,"is_corresponding":false},{"id":983200,"name":"Avisha Das","orcid":"0000-0002-5015-2665","position":0,"is_corresponding":true}],"reference_count":10,"raw_metadata":null,"created_at":"2026-07-19T02:09:03.883685Z","pmid":"38269887","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}