| LitCovid-OGER-BB | | Using OGER (www.ontogene.com) and Biobert to obtain annotations for 10 different vocabularies. | 308 K | Fabio Rinaldi | Nico Colic | 2023-11-28 | Released | |
| LitCovid-PAS-Enju | | Predicate-argument structure annotation produced by the Enju parser. | 125 K | | Jin-Dong Kim | 2023-11-28 | Beta | |
| LitCovid-PD-CHEBI | | | 1.43 M | | Jin-Dong Kim | 2023-11-24 | Developing | |
| LitCovid-PD-CLO | | | 3.73 M | | Jin-Dong Kim | 2023-11-24 | Developing | |
| LitCovid-PD-FMA-UBERON | | | 1.3 M | | Jin-Dong Kim | 2023-11-28 | Developing | |
| LitCovid-PD-FMA-UBERON-v1 | | PubDictionaries 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 K | | Jin-Dong Kim | 2023-11-27 | Released | |
| LitCovid-PD-GlycoEpitope | | | 999 | | Jin-Dong Kim | 2023-11-29 | Developing | |
| LitCovid-PD-GO-BP | | Terms for biological prosesses, as defined in GO | 374 K | | Jin-Dong Kim | 2023-11-29 | Developing | |
| LitCovid-PD-HP | | | 922 K | | Jin-Dong Kim | 2023-11-28 | Beta | |
| LitCovid-PD-HP-v1 | | PubDictionaries 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 K | | Jin-Dong Kim | 2023-11-29 | Released | |
| LitCovid-PD-MONDO | | | 2.26 M | | Jin-Dong Kim | 2023-11-24 | | |
| LitCovid-PD-MONDO-v1 | | PubDictionaries 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 K | | Jin-Dong Kim | 2023-11-29 | Released | |
| LitCovid-PD-UBERON | | | 540 K | | Jin-Dong Kim | 2023-11-29 | | |
| LitCovid-PMC-OGER-BB | | Annotating PMC articles with OGER and BioBert, according to an hand-crafted Covid-specific dictionary and the 10 different CRAFT ontologies (http://bionlp-corpora.sourceforge.net/CRAFT/):
Chemical Entities of Biological Interest (CHEBI),
Cell Ontology (CL),
Entrez Gene (UBERON),
Gene Ontology (biological process (GO-BP), cellular component (GO-CC), and molecular function (GO-MF),
NCBI Taxonomy (NCBITaxon),
Protein Ontology (PR),
Sequence Ontology (SO) | 3.14 M | Fabio Rinaldi | Nico Colic | 2023-11-24 | Developing | |
| LitCovid-PubTator | | | 5.88 M | | Jin-Dong Kim | 2023-11-24 | Beta | |
| LitCovid-PubTatorCentral | | Named-entities for the documents in the LitCovid dataset. Annotations were automatically predicted by the PubTatorCentral tool (https://www.ncbi.nlm.nih.gov/research/pubtator/) | 4.64 K | | zebet | 2023-11-27 | Released | |
| LitCovid-PubTator-s | | | 196 | | Jin-Dong Kim | 2023-11-29 | | |
| LitCovid-sample-CHEBI | | | 1.44 K | | Jin-Dong Kim | 2023-11-29 | Testing | |
| LitCovid-sample-docs | | 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
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
| 0 | | Jin-Dong Kim | 2023-11-29 | Uploading | |
| LitCovid-sample-DRON | | | 0 | | Jin-Dong Kim | 2023-11-29 | Testing | |
