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Jin-Dong Kim
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Collections
NameDescriptionUpdated at
1-10 / 12 show all
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
GlyCosmos600A random collection of 600 PubMed abstracts from 6 glycobiology-related journals: Glycobiology, Glycoconjugate journal, The Journal of biological chemistry, Journal of proteome research, Journal of proteomics, and Carbohydrate research. The whole PMIDs were collected on June 11, 2019. From each journal, 100 PMIDs were randomly sampled.2021-10-22
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
LitCovid-sampleVarious annotations to a sample set of LitCovid, to demonstrate potential of harmonized various annotations.2021-01-14
CORD-19-sample-annotation2020-04-21
LitCovid2021-10-18
LitCoin2021-12-14
CORD-19CORD-19 (COVID-19 Open Research Dataset) is a free, open resource for the global research community provided by the Allen Institute for AI: https://pages.semanticscholar.org/coronavirus-research. As of 2020-03-20, it contains over 29,000 full text articles. This CORD-19 collection at PubAnnotation is prepared for the purpose of collecting annotations to the texts, so that they can be easily accessed and utilized. If you want to contribute with your annotation, take the documents in the CORD-19_All_docs project, produce your annotation to the texts using your annotation system, and contribute the annotation back to PubAnnotation (HowTo). 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. Once you have uploaded your annotation, please notify it to admin@pubannotation.org admin@pubannotation.org, so that it can be included in this collection, which will make your annotation much easily findable. Note that as the CORD-19 dataset grows, the documents in this collection also will be updated. IMPORTANT: CORD-19 License agreement requires that the dataset must be used for text and data mining only.2020-04-14
Projects
Name TDescription# Ann.Updated atStatus
131-140 / 163 show all
NCBITAXONannotation for NCBI taxonomy. Automatic annotation by PD-NCBITaxon.1.1 M2024-09-18Developing
NGLY1-deficiencyA collection of PubMed abstracts that may be related to NGLY1 deficiency.60.5 K2023-11-29Developing
Parkinson542023-11-28Testing
performance-testa project for performance test480 K2023-11-27Testing
pmc-enju-pasPredicate-argument structure annotation produced by Enju. This data set is initially produced as a supporting resource for BioNLP-ST 2016 GE task. As so, it currently includes the 34 full paper articles that are in the benchmark data sets of GE 2016 task, reference data set (bionlp-st-ge-2016-reference) and test data set (bionlp-st-ge-2016-test), but will be extended to include more papers from the PubMed Central Open Access subset (PMCOA). 205 K2023-11-28Developing
Preeclampsia-compare67.2 K2023-11-29Testing
preeclampsia_genes17.8 K2023-11-29Developing
PubCasesCollectionabstracts in PubCases02023-11-29
PubMed-2000abstracts published in 2000.02023-11-29Developing
pubmed-2016abstracts published in 201602023-11-28
Automatic annotators
NameDescription
21-30 / 38 show all
discourse-simplifierA discourse analyzer developed by Univ. Manchester.
PD-FMA-PAE-BBatch mode annotator of PD-FMA-PAE
PD-GO-BP-BBiological Processes as defined in GO
EnjuParserEnju HPSG Parser developed by University of Tokyo.
PD-UBERON-AE-2023It annotates for anatomical entities, based on the UBERON-AE-2023 dictionary on PubDictionaries. Threshold is set to 0.85.
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-FMA-PAEPhysical Anatomical Entities from FMA
PD-CHEBIPubdictionaries annotation using the terms sourced from CHEBI, the 2020-03-31 version
PD-MONDOPubDictionaries annotation with the MONDO dictionary.
Editors
NameDescription
1-1 / 1
TextAEThe official stable version of TextAE.