• Medientyp: E-Artikel
  • Titel: PEDL+: protein-centered relation extraction from PubMed at your fingertip
  • Beteiligte: Weber, Leon [VerfasserIn]; Barth, Fabio [VerfasserIn]; Lorenz, Leonie [VerfasserIn]; Konrath, Fabian [VerfasserIn]; Huska, Kirsten [VerfasserIn]; Wolf, Jana [VerfasserIn]; Leser, Ulf [VerfasserIn]
  • Erschienen: Freie Universität Berlin: Refubium (FU Berlin), 2023
  • Sprache: Englisch
  • DOI: https://doi.org/10.17169/refubium-41823; https://doi.org/10.1093/bioinformatics/btad603
  • Schlagwörter: PubMed ; complex data analysis ; relation extraction
  • Entstehung:
  • Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Beschreibung: 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.
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Namensnennung (CC BY)