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Yue Wang
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NameDescriptionUpdated at
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DisGeNET5Associations obtained by text mining MEDLINE abstracts using the BeFree system2019-03-11
PIRProtein Information Resource (PIR)2019-03-12
AnEMthe largest manually annotated corpus on anatomical entities2019-04-03
Projects
Name TDescription# Ann.Updated atStatus
1-10 / 25 show all
TEST03.37 M2023-11-24
SCAI-TestA small corpus for the evaluation of dictionaries containing chemical entities. Publication: http://www.scai.fraunhofer.de/fileadmin/images/bio/data_mining/paper/kolarik2008.pdf Original source: https://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads/corpora-for-chemical-entity-recognition.html1.21 K2023-11-28Released
PIR-corpus2The protein tag was used to tag proteins, or protein-associated or -related objects, such as domains, pathways, expression of gene. Annotation guideline: http://pir.georgetown.edu/pirwww/about/doc/manietal.pdf5.52 K2023-11-29Released
PIR-corpus1The Protein Information Resource (PIR) is not biased towards any particular biomedical domain, and is expected to provide more diverse protein names in a given sample size. Annotation category: protein, compound-protein, acronym.4.44 K2023-11-27Released
PennBioIEThe 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).23.8 K2023-11-26Released
OryzaGPA dataset for Named Entity Recognition for rice gene29.1 K2023-11-24Uploading
jnlpba-st-trainingThe 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 1990~1999.51.1 K2023-11-26Released
GENIAcorpus multi_cell (1,782) mono_cell (222) virus (2,136) protein_family_or_group (8,002) protein_complex (2,394) protein_molecule (21,290) protein_subunit (942) protein_substructure (129) protein_domain_or_region (1,044) protein_other (97) peptide (521) amino_acid_monomer (784) DNA_family_or_group (332) DNA_molecule (664) DNA_substructure (2) DNA_domain_or_region (39) DNA_other (16) RNA_family_or_group (1,545) RNA_molecule (554) RNA_substructure (106) RNA_domain_or_region (8,237) RNA_other (48) polynucleotide (259) nucleotide (243) lipid (2,375) carbohydrate (99) other_organic_compound (4,113) body_part (461) tissue (706) cell_type (7,473) cell_component (679) cell_line (4,129) other_artificial_source (211) inorganic (258) atom (342) other (21,056) 78.9 K2023-11-29Released
funRiceGenes-exact8412023-11-28Developing
funRiceGenes-all1.51 K2023-11-29Developing
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