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User 'Jin-Dong Kim'


NameDescriptionUpdated at
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GlycoBiologyAnnotations made to the titles and abstracts of the journal 'GlycoBiology'2019-03-10
PreeclampsiaPreeclampsia-related annotations for text mining2019-03-10
bionlp-st-ge-2016The 2016 edition of the Genia event extraction (GE) task organized within BioNLP-ST 20162019-03-11


NameTDescription# Ann.Updated atStatus
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DocumentLevelAnnotationSampleA sample project for document level annotation472017-06-19Testing
ICD10Annotation for disease names as defined in ICD101.6 K2016-05-04Developing
EDAM-DFOannotation for EDAM terms for data, formats, and operations12.5 K2016-09-21Testing
GO-BPAnnotation for biological processes as defined in the "Biological Process" subset of Gene Ontology35.4 K2016-06-04Developing
GlycoBiology-GOGO-based annotation to GlycoBiology abstracts02016-06-11Testing
bionlp-st-ge-2016-corefCoreference annotation to the benchmark data set (reference and test) of BioNLP-ST 2016 GE task. For detailed information, please refer to the benchmark reference data set (bionlp-st-ge-2016-reference) and benchmark test data set (bionlp-st-ge-2016-test).8532016-05-23Released
GO-MFAnnotation for molecular functions as defined in the "Molecular Function" subtree of Gene Ontology19.7 K2016-05-03Testing
bionlp-st-ge-2016-test-proteinsProtein annotations to the benchmark test data set of the BioNLP-ST 2016 GE task. A participant of the GE task may import the documents and annotations of this project to his/her own project, to begin with producing event annotations. For more details, please refer to the benchmark test data set (bionlp-st-ge-2016-test). 4.34 K2016-05-04Released
EDAM-topicsannotation for EDAM topics11.6 K2016-09-21Testing
bionlp-st-ge-2016-referenceIt is the benchmark reference data set of the BioNLP-ST 2016 GE task. It includes Genia-style event annotations to 20 full paper articles which are about NFκB proteins. The task is to develop an automatic annotation system which can produce annotation similar to the annotation in this data set as much as possible. For evaluation of the performance of a participating system, the system needs to produce annotations to the documents in the benchmark test data set (bionlp-st-ge-2016-test). GE 2016 benchmark data set is provided as multi-layer annotations which include: bionlp-st-ge-2016-reference: benchmark reference data set (this project) bionlp-st-ge-2016-test: benchmark test data set (annotations are blined) bionlp-st-ge-2016-test-proteins: protein annotation to the benchmark test data set Following is supporting resources: bionlp-st-ge-2016-coref: coreference annotation bionlp-st-ge-2016-uniprot: Protein annotation with UniProt IDs. pmc-enju-pas: dependency parsing result produced by Enju UBERON-AE: annotation for anatomical entities as defined in UBERON ICD10: annotation for disease names as defined in ICD10 GO-BP: annotation for biological process names as defined in GO GO-CC: annotation for cellular component names as defined in GO A SPARQL-driven search interface is provided at http://bionlp.dbcls.jp/sparql.14.4 K2016-05-23Released

Automatic annotators

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TextSentencersentence segmentation
EnjuParserEnju HPSG Parser developed by University of Tokyo.
PD-UBERON-AE-BIt annotates for anatomical entities, based on the UBERON-AE dictionary on PubDictionaries. It used the default threshold, 0.85. It uses the batch mode annotation, and may be used for annotation to a large amount of documents.
PD-UBERON-AEIt annotates for anatomical entities, based on the UBERON-AE dictionary on PubDictionaries. Threshold is set to 0.85.
PD-GlycoEpitope-BA batch annotator using PubDictionaries with the dictionary 'GlycoEpitope'
PubTator-ChemicalTo pull the pre-computed chemical annotation from PubTator.
PubTator-GeneTo pull the pre-computed gene annotation from PubTator.
PubTator-SpeciesTo pull the pre-computed Species annotation from PubTator.


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TextAE-DevIt is a development version of TextAE. While this version has richer features, there is a chance of some bugs.
TextAEIt is a "Text Annotation Editor" developed by DBCLS. It is developed as a model implementation of PubAnnotation-interoperable viewer/editor.