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PEDL+: Protein-centered relation extraction from PubMed at your fingertip

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Item Type:Article
Title:PEDL+: Protein-centered relation extraction from PubMed at your fingertip
Creators Name:Weber, L., Barth, F., Lorenz, L., Konrath, F., Huska, K., Wolf, J. and Leser, U.
Abstract:Relation extraction (RE) from large text collections is an important tool for database curation, pathway reconstruction, or functional omics data analysis. In practice, RE often is part of a complex data analysis pipeline requiring specific adaptations like restricting the types of relations or the set of proteins to be considered. However, current systems are either non-programmable web sites or research code with fixed functionality. We present PEDL+, a user-friendly tool for extracting protein-protein and protein-chemical associations from PubMed articles. PEDL+ combines state-of-the-art NLP technology with adaptable ranking and filtering options and can easily be integrated into analysis pipelines. We evaluated PEDL+ in two pathway curation projects and found that 59% to 80% of its extractions were helpful.
Keywords:Factual Databases, PubMed, Software
Source:Bioinformatics
ISSN:1367-4803
Publisher:Oxford University Press
Volume:39
Number:11
Page Range:btad603
Date:November 2023
Official Publication:https://doi.org/10.1093/bioinformatics/btad603
PubMed:View item in PubMed

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