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Jin-Dong Kim
User info
Collections
NameDescriptionUpdated at
1-10 / 13 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
71-80 / 175 show all
LitCovid-PD-GlycoEpitope9992023-11-29Developing
LitCovid-PD-FMA-UBERON-v1PubDictionaries annotation for anatomy terms - updated at 2020-04-20 Disease term annotation based on FMA and Uberon. Version 2020-04-20. The terms in FMA and Uberon are loaded in PubDictionaries (FMA and Uberon), with which the annotations in this project are produced. The parameter configuration used for this project is here for FMA and there for Uberon. 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.4.3 K2023-11-27Released
LitCovid-PD-FMA-UBERON1.3 M2023-11-28Developing
LitCovid-PD-CLO3.73 M2023-11-24Developing
LitCovid-PD-CHEBI1.43 M2023-11-24Developing
LitCovid-PAS-EnjuPredicate-argument structure annotation produced by the Enju parser.125 K2023-11-28Beta
LitCovid-manual5402023-11-30Developing
LitCovid-GlycoBiologyArticles from GlycoBiology, received by the keyword "Covid-19"02023-11-29Testing
LitCovid-docs-s02023-11-29Released
LitCovid-docsUpdated at 2021-01-12 A comprehensive literature resource on the subject of Covid-19 is collected by NCBI: https://www.ncbi.nlm.nih.gov/research/coronavirus/ The LitCovid project@PubAnnotation is a collection of the titles and abstracts of the LitCovid dataset, for the people who want to perform text mining analysis. Please note that if you produce some annotation to the documents in this project, and contribute the annotation back to PubAnnotation, it will become publicly available together with contribution from other people. If you want to contribute your annotation to PubAnnotation, please refer to the documentation page: http://www.pubannotation.org/docs/submit-annotation/ The list of the PMID is sourced from here The 6 entries of the following PMIDs could not be included because they were not available from PubMed:32161394, 32104909, 32090470, 32076224, 32161394 32188956, 32238946. Below is a notice from the original LitCovid dataset: PUBLIC DOMAIN NOTICE National Center for Biotechnology Information This software/database is a "United States Government Work" under the terms of the United States Copyright Act. It was written as part of the author's official duties as a United States Government employee and thus cannot be copyrighted. This software/database is freely available to the public for use. The National Library of Medicine and the U.S. Government have not placed any restriction on its use or reproduction. Although all reasonable efforts have been taken to ensure the accuracy and reliability of the software and data, the NLM and the U.S. Government do not and cannot warrant the performance or results that may be obtained by using this software or data. The NLM and the U.S. Government disclaim all warranties, express or implied, including warranties of performance, merchantability or fitness for any particular purpose. Please cite the authors in any work or product based on this material : Chen Q, Allot A, & Lu Z. (2020) Keep up with the latest coronavirus research, Nature 579:193 182023-11-28Testing
Automatic annotators
NameDescription
1-10 / 40 show all
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.
PubTator-DiseaseTo pull the pre-computed disease annotation from PubTator.
PubTator-MutationTo pull the pre-computed mutation annotation from PubTator.
discourse-simplifierA discourse analyzer developed by Univ. Manchester.
PD-NGLY1-deficiency-BA batch annotator for NGLY1 deficiency
PD-UBERON-AEIt annotates for anatomical entities, based on the UBERON-AE dictionary on PubDictionaries. Threshold is set to 0.85.
PD-MONDOPubDictionaries annotation with the MONDO dictionary.
PD-FMA-PAEPhysical Anatomical Entities from FMA
Editors
NameDescription
1-1 / 1
TextAEThe official stable version of TextAE.