1TUM, Department of Informatics, Bioinformatics & Computational Biology - i12, Garching, Munich 85748, Germany2TUM Graduate School, Center of Doctoral Studies in Informatics and its Applications (CeDoSIA), Garching 85748, Germany3Microsoft, WA 98008, Bellevue, USA4Ludwig Maximilian University, 80538 Munich & Siemens AG, Corporate Technology, Munich 81739, Germany5BITS-Pilani K. K. Birla Goa Campus, Goa 403726, India6Concur (Germany) GmbH, Frankfurt am Main 60528, Germany7Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, L-4367 Belvaux, Luxembourg8Institute of Advanced Study (TUM-IAS) & Institute for Food and Plant Sciences WZW - Weihenstephan & New York Consortium on Membrane Protein Structure (NYCOMPS) & Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
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Motivation:The extraction of sequence variants from the literature remains an important task. Existing methods primarily target standard (ST) mutation mentions (e.g. ‘E6V’), leaving relevant mentions natural language (NL) largely untapped (e.g. ‘glutamic acid was substituted by valine at residue 6’).Results:We introduced three new corpora suggesting named-entity recognition (NER) to be more challenging than anticipated: 28-77% of all articles contained mentions only available in NL. Our new method nala captured NL and ST by combining conditional random fields with word embedding features learned unsupervised from the entire PubMed. In our hands, nala substantially outperformed the state-of-the-art. For instance, we compared all unique mentions in new discoveries correctly detected by any of three methods (SETH, tmVar, or nala). Neither SETH nor tmVar discovered anything missed by nala, while nala uniquely tagged 33% mentions. For NL mentions the corresponding value shot up to 100% nala-only.Availability and Implementation:Source code, API and corpora freely available at: http://tagtog.net/-corpora/IDP4+.Contact:email@example.comSupplementary information:Supplementary data are available at Bioinformatics online.