| cancer_precision | | for gene mutaiton and cancer therapy | 8 | | serenity | 2023-11-29 | Testing | |
| falsetest_150825 | | test | 0 | ichihara_hisako | Hisako Ichihara | 2015-09-11 | Testing | |
| namedentityrecognition | | | 0 | | white | 2016-05-13 | Testing | |
| Annotation-Euglena-Enzymes | | | 0 | | Shuichi Kawashima | 2016-06-13 | Developing | |
| NAKLEE | |
| 0 | | Nakyolee | 2017-07-13 | | |
| bionlp-st-pc-2013-training | | The training dataset from the pathway curation (PC) task in the BioNLP Shared Task 2013.
The entity types defined in the PC task are simple chemical, gene or gene product, complex and cellular component. | 7.86 K | NaCTeM and KISTI | Yue Wang | 2023-11-27 | Released | |
| Training_Data_English_fr_en | | | 0 | | wmtbio | 2023-11-29 | Developing | |
| kaiyin_test | | | 3.33 K | | zhoukaiyin | 2023-11-26 | | |
| AIMed | | The AIMed corpus is one of the most widely used corpora for protein-protein interaction extraction. The protein annotations are either parts of the protein interaction annotations, or are uninvolved in any protein interaction annotation.
Publication: http://www.cs.utexas.edu/~ml/papers/bionlp-aimed-04.pdf | 4.04 K | The University of Texas at Austin | Yue Wang | 2023-11-27 | Testing | |
| LitCovid-v1-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
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
| 0 | | Jin-Dong Kim | 2023-11-29 | Released | |
| Nalee | | trial version | 1 | | Nakyolee | 2023-11-28 | | |
| bionlp-ost-19-SeeDev-bin-test | | | 2.32 K | | ldeleger | 2023-11-28 | Developing | |
| GGDB-2020 | | | 2.44 K | | angata | 2023-11-30 | Developing | |
| Staphylococcus | | | 7.46 K | haruo | haruo | 2023-11-29 | Testing | |
| Gene_Chemical | | EMU abstract annotation | 0 | | zhoukaiyin | 2023-11-29 | Developing | |
| RDoCTask2SampleData | | Each annotation file contains an annotated abstract with the most relevant sentence. The relevant sentence is annotated with the RDoC category name. The annotation data are formatted as json files. Please refer to the following page for a more detailed description of the json format http://www.pubannotation.org/docs/annotation-format/.
| 10 | | mmanani1s | 2023-11-29 | Released | |
| bionlp-st-ge-2016-test-proteins | | Protein annotations to the benchmark test data set of the BioNLP-ST 2016 GE task.
A participant of the GE task may import the documents and annotations of this project to his/her own project, to begin with producing event annotations.
For more details, please refer to the benchmark test data set (bionlp-st-ge-2016-test).
| 4.34 K | DBCLS | Jin-Dong Kim | 2023-11-27 | Released | |
| LitCovid-PD-MONDO | | | 2.26 M | | Jin-Dong Kim | 2023-11-24 | | |
| testtesttest | | | 17.4 K | | Jin-Dong Kim | 2024-09-16 | Developing | |
| bayaba | | nalee | 7 | | Nakyolee | 2023-11-29 | | |
