| glycosmos-test-structure-v1 | | | 471 | | ISSAKU YAMADA | 2023-11-27 | Testing | |
| 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 | |
| LappsTest | | Project to test posting annotations directly from the Language Applications Grid | 2.67 K | Keith Suderman | ksuderman | 2023-11-27 | Developing | |
| GlyCosmos600-GlycoProteins | | GlycoProtein 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-docs | 3.68 K | | Jin-Dong Kim | 2023-11-27 | Testing | |
| PMID_GLOBAL | | Global sentencer tagging of public PMID abstracts.
Open and publicly available to the global community. | 2.24 M | | alo33 | 2023-11-24 | Developing | |
| bionlp-st-ge-2016-uniprot | | UniProt protein annotation to the benchmark data set of BioNLP-ST 2016 GE task: reference data set (bionlp-st-ge-2016-reference) and test data set (bionlp-st-ge-2016-test).
The annotations are produced based on a dictionary which is semi-automatically compiled for the 34 full paper articles included in the benchmark data set (20 in the reference data set + 14 in the test data set).
For detailed information about BioNLP-ST GE 2016 task data sets, please refer to the benchmark reference data set (bionlp-st-ge-2016-reference) and benchmark test data set (bionlp-st-ge-2016-test).
| 16.2 K | DBCLS | Jin-Dong Kim | 2023-11-29 | Beta | |
| LitCovid-docs | | Updated 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
| 18 | | Jin-Dong Kim | 2023-11-28 | Testing | |
| pmc-enju-pas | | Predicate-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 K | DBCLS | Jin-Dong Kim | 2023-11-28 | Developing | |
| LitCovid-sample-PD-UBERON | | PubDictionaries annotation for UBERON terms - updated at 2020-04-30
It is annotation for anatomical entities based on Uberon.
The terms in Uberon are uploaded in PubDictionaries
(Uberon),
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.
| 310 | | Jin-Dong Kim | 2023-11-28 | Beta | |
| GlyCosmos6-CLO | | Automatic annotation by PC-CLO. | 1.18 M | | Jin-Dong Kim | 2023-11-24 | Developing | |
| LitCovid-OGER | | Using OGER (http://www.ontogene.org/resources/oger) to detect entities from 10 different vocabularies | 9.31 K | Fabio Rinaldi | Nico Colic | 2023-11-29 | Released | |
| GlycoBiology-Epitope | | GlycoEpitope-based annotation to GlycoBiology abstracts | 3.18 K | Shujiro Okuda | shuo50 | 2023-11-29 | Testing | |
| GlyCosmos6-Glycan-Motif-Image | | | 87.8 K | | Jin-Dong Kim | 2023-11-24 | Developing | |
| PubTator4TogoVar | | | 198 K | PubTator | Yasunori Yamamoto | 2024-01-10 | Developing | |
| Text2LOD Test Project | | Text2LOD Test Project | 2 | Shuichi Kawashima | Shuichi Kawashima | 2023-11-30 | Testing | |
| Find2ER | | Find the Findings of Enzymatic Reaction | 0 | Akihiro Kameda | Akihiro Kameda | 2023-11-26 | Testing | |
