ArticleBioinformatics (Oxford, England)2024
STRING-ing together protein complexes: corpus and methods for extracting physical protein interactions from the biomedical literature.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
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- LSD600: the first corpus of biomedical abstracts annotated with lifestyle-disease relations.Database : the journal of biological databases and curation · 2025Article
- Lifestyle factors in the biomedical literature: an ontology and comprehensive resources for named entity recognition.Bioinformatics (Oxford, England) · 2024Article
- RegulaTome: a corpus of typed, directed, and signed relations between biomedical entities in the scientific literature.Database : the journal of biological databases and curation · 2024Article
- Metabolomic Profiling ofPharmaceuticals (Basel, Switzerland) · 2024Article
- CoNECo: a Corpus for Named Entity recognition and normalization of protein Complexes.Bioinformatics advances · 2024Article
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5 authors.
Funding
Abstract
motivationUnderstanding biological processes relies heavily on curated knowledge of physical interactions between proteins. Yet, a notable gap remains between the information stored in databases of curated knowledge and the plethora of interactions documented in the scientific literature.
resultsTo bridge this gap, we introduce ComplexTome, a manually annotated corpus designed to facilitate the development of text-mining methods for the extraction of complex formation relationships among biomedical entities targeting the downstream semantics of the physical interaction subnetwork of the STRING database. This corpus comprises 1287 documents with ∼3500 relationships. We train a novel relation extraction model on this corpus and find that it can highly reliably identify physical protein interactions (F1-score = 82.8%). We additionally enhance the model's capabilities through unsupervised trigger word detection and apply it to extract relations and trigger words for these relations from all open publications in the domain literature. This information has been fully integrated into the latest version of the STRING database. AVAILABILITY AND IMPLEMENTATION: We provide the corpus, code, and all results produced by the large-scale runs of our systems biomedical on literature via Zenodo https://doi.org/10.5281/zenodo.8139716, Github https://github.com/farmeh/ComplexTome_extraction, and the latest version of STRING database https://string-db.org/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.