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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
NameTDescription# Ann.Updated at Status
91-100 / 163 show all
LitCovid-PD-MONDO-v1PubDictionaries annotation for disease terms - updated at 2020-04-20 It is based on MONDO Version 2020-04-20. The terms in MONDO are loaded in PubDictionaries, with which the annotations in this project are produced. The parameter configuration used for this project is here. Note that it is an automatically generated dictionary-based annotation. It will be updated periodically, as the documents are increased, and the dictionary is improved.13.4 K2023-11-29Released
LitCovid-PD-HP-v1PubDictionaries annotation for human phenotype terms - updated at 2020-04-20 Disease term annotation based on HP. Version 2020-04-20. The terms in HP are loaded in PubDictionaries, with which the annotations in this project are produced. The parameter configuration used for this project is here. Note that it is an automatically generated dictionary-based annotation. It will be updated periodically, as the documents are increased, and the dictionary is improved.3.03 K2023-11-29Released
LitCoin-entities13.6 K2023-11-29Testing
Test-merged3.21 K2023-11-29
bionlp-st-ge-2016-reference-eval4262023-11-29Testing
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
EDAM-topicsannotation for EDAM topics11.6 K2023-11-29Testing
ggdb-test2.4 K2023-11-29Testing
CORD-19-PD-HPPubDictionaries annotation for HP terms - updated at 2020-04-30 Disease term annotation based on HP. Version 2020-04-20. The terms in HP are loaded in PubDictionaries, with which the annotations in this project are produced. The parameter configuration used for this project is here. Note that it is an automatically generated dictionary-based annotation. It will be updated periodically, as the documents are increased, and the dictionary is improved.1.15 M2023-11-29Released
GlycoBiology-Motifs4.15 K2023-11-29
Automatic annotators
NameDescription
21-30 / 38 show all
PubTatorPubTator annotation provided by NCBI
PD-CHEBI-B
PD-GlycoGenes20190927-B
PD-GO-BP-BBiological Processes as defined in GO
PD-CLO-B
PD-HP-PA-B
PD-NCBIGene
PD-GlycoEpitope-BA batch annotator using PubDictionaries with the dictionary 'GlycoEpitope'
PD-HP-PA
Glycan-Motif-Image
Editors
NameDescription
1-1 / 1
TextAEThe official stable version of TextAE.