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NameTDescription# Ann.AuthorMaintainer Updated_atStatus

41-60 / 593 show all
bionlp-st-epi-2011-training The training dataset from the Epigenetics and Post-translational Modifications (EPI) task in the BioNLP Shared Task 2011. The core entities of the task are genes and gene products (RNA and proteins), identified in the data simply as "Protein" annotations. 7.59 KGENIAYue Wang2023-11-29Released
bionlp-st-id-2011-training The training dataset from the infectious diseases (ID) task in the BioNLP Shared Task 2011. Entity types: - Genes and gene products: gene, RNA, and protein name mentions. - Two-component systems: mentions of the names of two-component regulatory systems, frequently embedding the names of the two Proteins forming the system.- Chemicals: mentions of chemical compounds such as "NaCL".- Organisms: mentions of organism names or organism specification through specific properties (e.g. "graRS mutant").- Regulons/Operons: mentions of names of specific regulons and operons.5.61 KUniversity of Tokyo Tsujii Laboratory, NaCTeM and Biocomplexity Institute of Virginia TechYue Wang2023-11-28Released
AIMed The AIMed corpus is one of the most widely used corpora for protein-protein interaction extraction. The protein annotations are either parts of the protein interaction annotations, or are uninvolved in any protein interaction annotation. Publication: http://www.cs.utexas.edu/~ml/papers/bionlp-aimed-04.pdf4.04 KThe University of Texas at AustinYue Wang2023-11-27Testing
funRiceGenes-exact 841Yue Wang2023-11-28Developing
AnEM_full-texts 250 documents selected randomly from full-text papers Entity types: organism subdivision, anatomical system, organ, multi-tissue structure, tissue, cell, developing anatomical structure, cellular component, organism substance, immaterial anatomical entity and pathological formation Together with AnEM_abstracts, it is probably the largest manually annotated corpus on anatomical entities.687NaCTeMYue Wang2023-11-29Uploading
SCAI-Test A 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 KCALBC ProjectYue Wang2023-11-28Released
CyanoBase Cyanobacteria are prokaryotic organisms that have served as important model organisms for studying oxygenic photosynthesis and have played a significant role in the Earthfs history as primary producers of atmospheric oxygen. Publication: http://www.aclweb.org/anthology/W12-24301.1 KKazusa DNA Research Institute and Database Center for Life Science (DBCLS)Yue Wang2023-11-26Released
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 1990~1999.51.1 KGENIAYue Wang2023-11-26Released
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).23.8 KUPenn Biomedical Information Extraction ProjectYue Wang2023-11-26Released
TEST0 3.37 MYue Wang2023-11-24
bionlp-st-bb3-2016-training Entity (bacteria, habitats and geographical places) annotation to the training dataset of the BioNLP-ST 2016 BB task. For more information, please refer to bionlp-st-bb3-2016-development and bionlp-st-bb3-2016-test. Bacteria 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. Habitat 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. Geographical Geographical entities are geographical and organization places denoted by official names.1.28 KINRAYue Wang2023-11-29Released
0mytest 144Yue Wang2023-11-29
PIR-corpus2 The 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 KUniversity of Delaware and Georgetown University Medical CenterYue Wang2023-11-29Released
FA_Top100Plus-GeneProtein Top100+本来Top100に入るべきだった7レビューの計、107レビュー中101レビュー。 5414, 6076, 6930, 8403, 9643, 18544は、0denotationでドキュメント自体登録していない。 attributesの詳細はconfig参照。 ドキュメントのソースDBが@AikoHIRAKIとなっているものはTypo修正がPubAnnotationの公式FirstAuthorsドキュメントに反映された段階で置き換えます。 10.4 Kyucca2023-11-29Uploading
PMC-KEGG Documents from PMC including the word KEGG, with names of software tools and databases marked. 27yucca2023-11-28Developing
LitCoin-Chemical-MeSH-CHEBI ChemicalEntity: Annotated by PD-MeSH2022_CHEBI_tuned-B3.84 Kyucca2023-11-29Testing
LitCoin-Disease-Tuning-1 Annotator=PD-MeSH2022_C_F03_plus_allFN-B6.98 Kyucca2023-11-29
test-integbio 0yucca2016-08-03
LitCoin-MeSH-Disease-2 Flase Negative全部入れてみた4.08 Kyucca2023-11-29
TEST-ChemicalEntity ChemicalEntity : Annotated by PD-MeSH2022_CHEBI_tuned-B827yucca2023-11-29Beta
NameT# Ann.AuthorMaintainer Updated_atStatus

41-60 / 593 show all
bionlp-st-epi-2011-training 7.59 KGENIAYue Wang2023-11-29Released
bionlp-st-id-2011-training 5.61 KUniversity of Tokyo Tsujii Laboratory, NaCTeM and Biocomplexity Institute of Virginia TechYue Wang2023-11-28Released
AIMed 4.04 KThe University of Texas at AustinYue Wang2023-11-27Testing
funRiceGenes-exact 841Yue Wang2023-11-28Developing
AnEM_full-texts 687NaCTeMYue Wang2023-11-29Uploading
SCAI-Test 1.21 KCALBC ProjectYue Wang2023-11-28Released
CyanoBase 1.1 KKazusa DNA Research Institute and Database Center for Life Science (DBCLS)Yue Wang2023-11-26Released
jnlpba-st-training 51.1 KGENIAYue Wang2023-11-26Released
PennBioIE 23.8 KUPenn Biomedical Information Extraction ProjectYue Wang2023-11-26Released
TEST0 3.37 MYue Wang2023-11-24
bionlp-st-bb3-2016-training 1.28 KINRAYue Wang2023-11-29Released
0mytest 144Yue Wang2023-11-29
PIR-corpus2 5.52 KUniversity of Delaware and Georgetown University Medical CenterYue Wang2023-11-29Released
FA_Top100Plus-GeneProtein 10.4 Kyucca2023-11-29Uploading
PMC-KEGG 27yucca2023-11-28Developing
LitCoin-Chemical-MeSH-CHEBI 3.84 Kyucca2023-11-29Testing
LitCoin-Disease-Tuning-1 6.98 Kyucca2023-11-29
test-integbio 0yucca2016-08-03
LitCoin-MeSH-Disease-2 4.08 Kyucca2023-11-29
TEST-ChemicalEntity 827yucca2023-11-29Beta