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Jin-Dong Kim
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Collections
Name DescriptionUpdated at
11-12 / 12 show all
LitCovid-v1This collection includes the result from the Covid-19 Virtual Hackathon. LitCovid is a comprehensive literature resource on the subject of Covid-19 collected by NCBI: https://www.ncbi.nlm.nih.gov/research/coronavirus/ Since the literature dataset was released, several groups are producing annotations to the dataset. To facilitate a venue for aggregating the valuable resources which are highly relevant to each other, and should be much more useful when they can be accessed together, this PubAnnotation collection is set up. It is a part of the Covid19-PubAnnotation project. In this collection, the LitCovid-docs project contains all the documents contained in the LitCovid literature collection, and the other projects are annotation datasets contributed by various groups. It is an open collection, which means anyone who wants to contribute can do so, in the following way: take the documents in the, LitCovid-docs project produce annotation to the texts based on your resource, and contribute the annotation back to this collection: create your own project at PubAnnotaiton, upload your annotation to the project (HowTo), and add the project to this collection. All the contributed annotations will become publicly available. Please note that, during uploading your annotation data, you do not need to be worried about slight changes in the text: PubAnnotation will automatically catch them and adjust the positions appropriately. Should you have any question, please feel free to mail to admin@pubannotation.org. 2020-11-20
PreeclampsiaPreeclampsia-related annotations for text mining2019-03-10
Projects
NameTDescription# Ann.Updated atStatus
121-130 / 163 show all
GO-BPAnnotation for biological processes as defined in the "Biological Process" subset of Gene Ontology35.4 K2023-11-29Developing
GO-MFAnnotation for molecular functions as defined in the "Molecular Function" subtree of Gene Ontology19.7 K2023-12-04Testing
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 K2023-11-29Released
Glycosmos6-MATAutomatic annotation by PD-MAT.263 K2023-11-29Developing
GlycosmosP-GlycoEpitope242023-11-29Testing
sentencesSentence segmentation annotation. Automatic annotation by TextSentencer.6.96 M2023-11-24Developing
Test-Documents12023-11-24
GlyCosmosP-Glycan-Motif82023-11-24Developing
MENA-example232023-11-24Testing
Glycosmos6-GlycoEpitopeAutomatic annotation by PD-GlycoEpitope.19.9 K2023-11-28Developing
Automatic annotators
NameDescription
11-20 / 38 show all
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-GlycanStructures-B
PD-GlycoGenes-B
PD-GlycoProteins-B
PD-FMA-PAE-BBatch mode annotator of PD-FMA-PAE
PD-Preeclampsia-B
PD-MONDO-BPubDictionaries annotation with the MONDO dictionary. Asynchronous protocol.
EnjuParserEnju HPSG Parser developed by University of Tokyo.
PD-CHEBIPubdictionaries annotation using the terms sourced from CHEBI, the 2020-03-31 version
PD-NCBITaxon-B
Editors
NameDescription
1-1 / 1
TextAEThe official stable version of TextAE.