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Projects (161)

Name Description # Ann. Author Maintainer updated at Status
bionlp-st-bb3-2016-training <p>Entity (bacteria, habitats and geographical places) annotation to the training dataset of the BioNLP-ST 2016 BB task. </p> <p>For more information, please refer to <a href="http://pubannotation.org/projects/bionlp-st-bb3-2016-development">bionlp-st-bb3-2016-development</a> and <a href="http://pubannotation.org/projects/bionlp-st-bb3-2016-test">bionlp-st-bb3-2016-test</a>. </p> <p><b>Bacteria</b></p> <p>Bacteria entities are annotated as contiguous spans of text that contains a full unambiguous prokaryote taxon name, the type label is Bacteria. The Bacteria type is a taxon, at any taxonomic level from phylum (Eubacteria) to strain. The category that the text entities have to be assigned to is the most specific and unique category of the NCBI taxonomy resource. In case a given strain, or a group of strains is not referenced by NCBI, it is assigned with the closest taxid in the taxonomy.</p> <p><b>Habitat</b></p> <p>Habitat entities are annotated as spans of text that contains a complete mention of a potential habitat for bacteria, the type label is Habitat. Habitat entities are assigned one or several concepts from the habitat subpart of the OntoBiotope ontology. The assigned concepts are as specific as possible. OntoBiotope defines most relevant microorganism habitats from all areas considered by microbial ecology (hosts, natural environment, anthropized environments, food, medical, etc.). Habitat entities are rarely referential entities, they are usually noun phrases including properties and modifiers. There are rare cases of habitats referred with adjectives or verbs. The spans are generally contiguous but some of them are discontinuous in order to cope with conjunctions.</p> <p><b>Geographical</b></p> <p>Geographical entities are geographical and organization places denoted by official names.</p> 1,292 INRA Yue Wang 2017-05-22 Released
bionlp-st-id-2011-training The training dataset from the infectious diseases (ID) task in the BioNLP Shared Task 2011. <br> Entity types: <br>- Genes and gene products: gene, RNA, and protein name mentions. <br>- Two-component systems: mentions of the names of two-component regulatory systems, frequently embedding the names of the two Proteins forming the system.<br>- Chemicals: mentions of chemical compounds such as "NaCL".<br>- Organisms: mentions of organism names or organism specification through specific properties (e.g. "graRS mutant").<br>- Regulons/Operons: mentions of names of specific regulons and operons. 5,609 University of Tokyo Tsujii Laboratory, NaCTeM and Biocomplexity Institute of Virginia Tech Yue Wang 2017-04-18 Released
jnlpba-st-training The training data used in the task came from the GENIA version 3.02 corpus, This was formed from a controlled search on MEDLINE using the MeSH terms "human", "blood cells" and "transcription factors". From this search, 1,999 abstracts were selected and hand annotated according to a small taxonomy of 48 classes based on a chemical classification. Among the classes, 36 terminal classes were used to annotate the GENIA corpus. For the shared task only the classes protein, DNA, RNA, cell line and cell type were used. The first three incorporate several subclasses from the original taxonomy while the last two are interesting in order to make the task realistic for post-processing by a potential template filling application. The publication year of the training set ranges over 1990~1999. 51,290 GENIA Yue Wang 2017-04-14 Released
SCAI-Test A small corpus for the evaluation of dictionaries containing chemical entities. <br> Publication: http://www.scai.fraunhofer.de/fileadmin/images/bio/data_mining/paper/kolarik2008.pdf <br> Original source: https://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads/corpora-for-chemical-entity-recognition.html 1,206 CALBC Project Yue Wang 2017-04-03 Released
BioLarkPubmedHPO 228 abstracts manually annotated with Human Phenotype Ontology (HPO) concepts and harmonized by three curators, which can be used as a reference standard for free text annotation of human phenotypes. For more info, please see Groza et al. "Automatic concept recognition using the human phenotype ontology reference and test suite corpora", 2015. 7,236 Tudor Groza simon 2017-03-28 Released
FSU-PRGE A new broad-coverage corpus composed of 3,306 MEDLINE abstracts dealing with gene and protein mentions.<br> The annotation process was semi-automatic. <br> Publication: http://aclweb.org/anthology/W/W10/W10-1838.pdf 59,505 CALBC Project Yue Wang 2017-03-08 Released
PIR-corpus2 The protein tag was used to tag proteins, or protein-associated or -related objects, such as domains, pathways, expression of gene.<br> Annotation guideline: http://pir.georgetown.edu/pirwww/about/doc/manietal.pdf 5,521 University of Delaware and Georgetown University Medical Center Yue Wang 2017-03-07 Released
LocText The manually annotated corpus consists of 100 PubMed abstracts annotated for proteins, subcellular localizations, organisms and relations between them. The focus of the corpus is on annotation of proteins and their subcellular localizations. 2,290 Goldberg et al Shrikant Vinchurkar 2017-01-20 Released
PennBioIE The PennBioIE corpus (0.9) covers two domains of biomedical knowledge. One is the inhibition of the cytochrome P450 family of enzymes (CYP450 or CYP for short) , and the other domain is the molecular genetics of dance (oncology or onco for short). 23,881 UPenn Biomedical Information Extraction Project Yue Wang 2016-12-06 Released
bionlp-st-cg-2013-training The training dataset from the cancer genetics task in the BioNLP Shared Task 2013. <br> Composed of anatomical and molecular entities. 10,935 NaCTeM Yue Wang 2016-12-06 Released