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Jin-Dong Kim
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NameDescriptionUpdated at
11-12 / 12 show all
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
Glycosmos6This collection contains annotation projects which target all the PubMed abstracts (at the time of January 14, 2022) from the 6 glycobiology-related journals: Glycobiology Glycoconjugate journal The Journal of biological chemistry Journal of proteome research Journal of proteomics Carbohydrate research 2023-11-16
Projects
NameTDescription # Ann.Updated atStatus
31-40 / 159 show all
UBERON-AEAnnotation for anatomical entities based on the "Anatomical Entity" subtree of UBERON ontology. Annotations are automatically produced using PubDictionaries with threshold: 0.85.859 K2023-11-29Developing
CORD-19_All_docsAll the documents in the whole CORD-19 dataset. The documents in this project will be updated as the CORD-19 dataset grows. See the COVID DATASET LICENSE AGREEMENT.02023-11-29Released
LitCovid-sample-docsA 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 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 02023-11-29Uploading
LitCovid-v1-docsA 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 02023-11-29Released
KoreanFN-exampleKorean FrameNet example62023-11-29Developing
LitCoin-GeneOrGeneProduct-v0https://pubdictionaries.org/text_annotation.json?dictionary=NCBIGene-NER&threshold=0.85&abbreviation=true15.8 K2023-11-29
GlycoBiology-GOGO-based annotation to GlycoBiology abstracts02023-11-29Testing
GlyCosmos600-GlycoProteinsGlycoProtein annotations were made using the glycoprotein-name dictionary on PubDictionaries: http://pubannotation.org/projects/GlyCosmos600-docs The documents were imported from the GlyCosmos600-docs project: http://pubannotation.org/projects/GlyCosmos600-docs3.68 K2023-11-27Testing
LitCoin-GeneOrGeneProduct-v3GeneOrGeneProduct after false positive control4.67 K2023-11-24
GlycoBiology-FMAFMA ontology-based annotation to GlycoBiology abstracts96.3 K2023-11-29Testing
Automatic annotators
NameDescription
11-20 / 38 show all
PD-FMA-PAEPhysical Anatomical Entities from FMA
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
Editors
NameDescription
1-2 / 2
TextAE-oldTextAE version 4, which was the latest stable version until Apr. 19, 2020.
TextAETextAE version 5, which enables edition of attributes of denotations.