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NameT Description# Ann.AuthorMaintainerUpdated_atStatus

401-420 / 557 show all
cancer_precision for gene mutaiton and cancer therapy8serenity2023-11-29Testing
falsetest_150825 test0ichihara_hisakoHisako Ichihara2015-09-11Testing
namedentityrecognition 0white2016-05-13Testing
Annotation-Euglena-Enzymes 0Shuichi Kawashima2016-06-13Developing
NAKLEE 0Nakyolee2017-07-13
bionlp-st-pc-2013-training The training dataset from the pathway curation (PC) task in the BioNLP Shared Task 2013. The entity types defined in the PC task are simple chemical, gene or gene product, complex and cellular component.7.86 KNaCTeM and KISTIYue Wang2023-11-27Released
bionlp-st-gro-2013-training The training data set of the BioNLP-ST 2013 GRO task, including 150 MEDLINE abstracts that are annotated with concepts and relations of the Gene Regulation Ontology (GRO; http://www.ebi.ac.uk/Rebholz-srv/GRO/GRO.html)8.02 KJung-jae KimJung-jae Kim2023-11-29Testing
kaiyin_test 3.33 Kzhoukaiyin2023-11-26
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
Training_Data_English_zh_en 0wmtbio2023-11-29Developing
Nalee trial version 1Nakyolee2023-11-28
bionlp-ost-19-SeeDev-bin-test 2.32 Kldeleger2023-11-28Developing
Training_Data_English_fr_en 0wmtbio2023-11-29Developing
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
Gene_Chemical EMU abstract annotation0zhoukaiyin2023-11-29Developing
RDoCTask2SampleData Each annotation file contains an annotated abstract with the most relevant sentence. The relevant sentence is annotated with the RDoC category name. The annotation data are formatted as json files. Please refer to the following page for a more detailed description of the json format http://www.pubannotation.org/docs/annotation-format/. 10mmanani1s2023-11-29Released
GGDB-2020 2.44 Kangata2023-11-30Developing
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
Staphylococcus 7.46 Kharuoharuo2023-11-29Testing
bayaba nalee7Nakyolee2023-11-29
NameT # Ann.AuthorMaintainerUpdated_atStatus

401-420 / 557 show all
cancer_precision 8serenity2023-11-29Testing
falsetest_150825 0ichihara_hisakoHisako Ichihara2015-09-11Testing
namedentityrecognition 0white2016-05-13Testing
Annotation-Euglena-Enzymes 0Shuichi Kawashima2016-06-13Developing
NAKLEE 0Nakyolee2017-07-13
bionlp-st-pc-2013-training 7.86 KNaCTeM and KISTIYue Wang2023-11-27Released
bionlp-st-gro-2013-training 8.02 KJung-jae KimJung-jae Kim2023-11-29Testing
kaiyin_test 3.33 Kzhoukaiyin2023-11-26
AIMed 4.04 KThe University of Texas at AustinYue Wang2023-11-27Testing
Training_Data_English_zh_en 0wmtbio2023-11-29Developing
Nalee 1Nakyolee2023-11-28
bionlp-ost-19-SeeDev-bin-test 2.32 Kldeleger2023-11-28Developing
Training_Data_English_fr_en 0wmtbio2023-11-29Developing
CyanoBase 1.1 KKazusa DNA Research Institute and Database Center for Life Science (DBCLS)Yue Wang2023-11-26Released
Gene_Chemical 0zhoukaiyin2023-11-29Developing
RDoCTask2SampleData 10mmanani1s2023-11-29Released
GGDB-2020 2.44 Kangata2023-11-30Developing
bionlp-st-bb3-2016-training 1.28 KINRAYue Wang2023-11-29Released
Staphylococcus 7.46 Kharuoharuo2023-11-29Testing
bayaba 7Nakyolee2023-11-29