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BioCreative specifications


Unique identifier OMICS_13658
Name BioCreative
Alternative name Critical Assessment of Information Extraction systems in Biology
Interface Application programming interface
Restrictions to use None
Computer skills Advanced
Version 5.0
Stability Stable
Maintained Yes


  • person_outline Cecilia Arighi

Publications for Critical Assessment of Information Extraction systems in Biology

BioCreative citations


Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature

J Biomed Semantics
PMCID: 5896136
PMID: 29650041
DOI: 10.1186/s13326-018-0181-1

[…] The BioCreative (Critical Assessment of Information Extraction systems in Biology) challenge [] focuses on recognition of entities in text (i.e. NER) as well as relation extraction. For BioCreative II, Smith et al. [] […]


Textpresso Central: a customizable platform for searching, text mining, viewing, and curating biomedical literature

BMC Bioinformatics
PMCID: 5845379
PMID: 29523070
DOI: 10.1186/s12859-018-2103-8

[…] spond to the needs of biocurators and the text mining community. Much effort has been devoted to understanding the critical needs of the biocuration workflow. Through community-wide endeavors such as BioCreative (Critical Assessment of Information Extraction in Biology), the biocuration and text mining communities have come together to determine the ways in which text mining tools can assist in th […]


Bio SimVerb and Bio SimLex: wide coverage evaluation sets of word similarity in biomedicine

BMC Bioinformatics
PMCID: 5800055
PMID: 29402212
DOI: 10.1186/s12859-018-2039-z

[…] We assess our representation models using a NER task with four established corpora: the Anatomical Entity Mention corpus (AnatEM) [], the BioCreative II Gene Mention task corpus (BC2GM) [], the BioCreative IV Chemical and Drug NER corpus (BC4CHEMD) and the JNLPBA corpus (JNLPBA) [].The NER model follows the simple window-based feed-forw […]


Exploiting graph kernels for high performance biomedical relation extraction

J Biomed Semantics
PMCID: 5791373
PMID: 29382397
DOI: 10.1186/s13326-017-0168-3

[…] f our two relation extraction subsystems. The column “All Relations” represents the performance of the final relation extraction system over the full CDR test data, that corresponds to the subtask of BioCreative-V []. […]


Disease named entity recognition from biomedical literature using a novel convolutional neural network

BMC Med Genomics
PMCID: 5751782
PMID: 29297367
DOI: 10.1186/s12920-017-0316-8

[…] corpus and 2 h for the CDR corpus.We validated the effectiveness of MCNN by applying it to two corpora containing both mention-level and concept-level annotations: the NCBI Disease corpus [] and the BioCreative V Chemical Disease Relation task (CDR) corpus []. Overall statistics for each dataset are provided in Table . The NCBI Disease corpus consists of 793 Medline abstracts separated into train […]


Collaborative relation annotation and quality analysis in Markyt environment

PMCID: 5737204
PMID: 29220479
DOI: 10.1093/database/bax090
call_split See protocol

[…] documents in TSV and BioC inline XML []. Moreover, the tool is able to import annotations following the formats BRAT standoff annotation [], BioC inline XML [], BioNLP standoff representation [] and BioCreative TSV []. Both documents and annotations are stored in the relational database supporting Markyt operations. Document contents are saved in HTML format with UTF-8 encoding which ensures mult […]


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BioCreative institution(s)
Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, USA; Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA; International Centre of Health Information Technology, Taipei Medical University, Taipei, Taiwan; DETI/IEETA, University of Aveiro, Campus Universitario de Santiago, Aveiro, Portugal; National Centre for Text Mining, University of Manchester, Manchester, UK; Facultad de Ciencias, Universidad Nacional Autonoma de Mexico, Ciudad de Mexico, Mexico; BMD Software, Aveiro, Portugal; Northern Institute for Cancer Research, Newcastle University, New Castle, UK; Rutgers University-Camden, Camden, NJ, USA; Centro de Ciencias Genomicas, Universidad Nacional Autonoma de Mexico, Ciudad de Mexico, Mexico; Department of Botany and Plant Pathology, Oregon State University Corvallis, OR, USA; Department of Computer Science and Information Engineering, National Taitung University, Taitung, Taiwan; College of Agriculture and Natural Resources, University of Delaware, Newark, DE, USA; Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany; SourceData, EMBO, Heidelberg, Germany; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, UK; Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Life Science Informatics, University of Bonn, Bonn, Germany; Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Prince of Wales Clinical School, University of New South Wales NSW, Sydney, NSW, Australia; SRI International, Menlo Park, CA, USA; Oxford e-Research Centre, University of Oxford, Oxford, UK; Department of Informatics and Bio-Computing, Ontario Institute for Cancer Research, Toronto, ON, Canada; HGMD, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, UK; Department of Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu, India; Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece; Microbial Genomics and Bioinformatics Group, Max Planck Institute for Marine Microbiology, Bremen, Germany; Innovation Center for Biomedical Informatics (ICBI), Georgetown University, WA, DC, USA; Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland; GMGF, Aix-Marseille Université, Marseille, France; Inserm, Marseille, France; Department of Medical Sciences, iBiMED and IEETA, University of Aveiro, Aveiro, Portugal; Taipei Medical University Graduate Institute of Biomedical informatics, Taipei, Taiwan; Department of Genetics, University of Cambridge, Cambridge, UK; Institute of Information Science, Academia Sinica, Taipei, Taiwan; Freelance Scientific Curator, Cleveland, OH, USA; Institute of Sport and Physical Activity Research (ISPAR), University of Bedfordshire, Bedford, UK; Ontology Development Group, Oregon Health & Science University, Portland, OR, USA; WormBase Consortium, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada; Medical College of Wisconsin, Milwaukee, WI, USA; Reed Elsevier, Philadelphia, PA, USA; European Bioinformatics Institute, Hinxton, UK; Roche Innovation Center Basel, Basel, Switzerland; National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA; MaizeGDB USDA ARS and University of Missouri, Columbia, MO, USA; The MITRE Corporation, Bedford, MA, USA
BioCreative funding source(s)
National Institutes of Health [R13GM109648, P41HG003751 and U54GM114833]; Intramural Research Program at National Library of Medicine; National Institutes of Health Office of Director [R24OD011883]; the US Department of Energy [DE-SC0010838]; National Science Foundation [#1340112, DBI#1356374]; Ontario Research Fund; the European Molecular Biology Laboratory; Facultad de Ciencias, UNAM.

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