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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 Evaluation of chemical and gene/protein entity recognition systems at BioCreative V.5: the CEMP and GPRO patents tracks Pérez-Pérez, Martin; Rabal, Obdulia; Pérez-Rodríguez, Gael. - 2017 BASE Show details 2 The CHEMDNER corpus of chemicals and drugs and its annotation principles Krallinger, Martin; Rabal, Obdulia; Leitner, Florian. - : BioMed Central, 2015 BASE Show details 3 CHEMDNER: The drugs and chemical names extraction challenge Krallinger, Martin; Leitner, Florian; Rabal, Obdulia. - : BioMed Central, 2015 BASE Show details 4 How to link ontologies and protein–protein interactions to literature: text-mining approaches and the BioCreative experience Krallinger, Martin; Leitner, Florian; Vazquez, Miguel; Salgado, David; Marcelle, Christophe; Tyers, Mike; Valencia, Alfonso; Chatr-aryamontri, Andrew. - : Oxford University Press, 2012 Abstract: There is an increasing interest in developing ontologies and controlled vocabularies to improve the efficiency and consistency of manual literature curation, to enable more formal biocuration workflow results and ultimately to improve analysis of biological data. Two ontologies that have been successfully used for this purpose are the Gene Ontology (GO) for annotating aspects of gene products and the Molecular Interaction ontology (PSI-MI) used by databases that archive protein–protein interactions. The examination of protein interactions has proven to be extremely promising for the understanding of cellular processes. Manual mapping of information from the biomedical literature to bio-ontology terms is one of the most challenging components in the curation pipeline. It requires that expert curators interpret the natural language descriptions contained in articles and infer their semantic equivalents in the ontology (controlled vocabulary). Since manual curation is a time-consuming process, there is strong motivation to implement text-mining techniques to automatically extract annotations from free text. A range of text mining strategies has been devised to assist in the automated extraction of biological data. These strategies either recognize technical terms used recurrently in the literature and propose them as candidates for inclusion in ontologies, or retrieve passages that serve as evidential support for annotating an ontology term, e.g. from the PSI-MI or GO controlled vocabularies. Here, we provide a general overview of current text-mining methods to automatically extract annotations of GO and PSI-MI ontology terms in the context of the BioCreative (Critical Assessment of Information Extraction Systems in Biology) challenge. Special emphasis is given to protein–protein interaction data and PSI-MI terms referring to interaction detection methods. Keyword: Original Article URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3309177 http://www.ncbi.nlm.nih.gov/pubmed/22438567 https://doi.org/10.1093/database/bas017 BASE Hide details 5 Benchmarking of the 2010 BioCreative Challenge III text-mining competition by the BioGRID and MINT interaction databases Krallinger, Martin; Vazquez, Miguel; Leitner, Florian... In: Krallinger, Martin; Vazquez, Miguel; Leitner, Florian; Salgado, David; Chatr-aryamontri, Andrew; Winter, Andrew; et al.(2011). Benchmarking of the 2010 BioCreative Challenge III text-mining competition by the BioGRID and MINT interaction databases. BMC Bioinformatics, 12(Suppl 8), S3. doi: http://dx.doi.org/10.1186/1471-2105-12-S8-S3. Retrieved from: http://www.escholarship.org/uc/item/44z3n3v1 (2011) BASE Show details 6 The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text Krallinger, Martin; Vazquez, Miguel; Leitner, Florian... In: ISSN: 1471-2105 ; BMC Bioinformatics ; https://hal.archives-ouvertes.fr/hal-01780325 ; BMC Bioinformatics, BioMed Central, 2011, 12 (Suppl 8), ⟨10.1186/1471-2105-12-S8-S3⟩ (2011) BASE Show details 7 A. Gatti: el lenguaje y sus poderes López Vázquez, Miguel Angel In: Archivum. - Oviedo : Univ. 57 (2007), 123-138 BLLDB Show details

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