MyTest | | | 9.81 M | | Jin-Dong Kim | 2023-11-24 | Testing | |
Allie | | An annotation set of abbreviations and expanded forms extracted from PubMed/MEDLINE by machines. | 8.7 M | Database Center for Life Science | Yasunori Yamamoto | 2023-11-24 | Developing | |
LitCovid-sentences | | | 5.63 M | | Jin-Dong Kim | 2023-11-24 | Developing | |
CORD-19_Custom_license_subset | | The Custom license subset of the CORD-19 dataset.
The documents in this project will be updated as the CORD-19 dataset grows.
See the COVID DATASET LICENSE AGREEMENT. | 5.08 M | | Jin-Dong Kim | 2023-11-24 | Released | |
PubCasesHPO | | HPO annotation in PubCases | 3.18 M | | Toyofumi Fujiwara | 2023-11-24 | Beta | |
CORD-19-PD-UBERON | | PubDictionaries annotation for UBERON terms - updated at 2020-04-30
It is disease term annotation 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. | 1.42 M | | Jin-Dong Kim | 2023-11-24 | Released | |
Epistemic_Statements | | The goal of this work is to identify epistemic statements in the scientific literature. An epistemic statement is a statement of unknowns, hypotheses, speculations, uncertainties, including statements of claims, hypotheses, questions, explanations, future opportunities, surprises, issues, or concerns within a sentence. The unit of an epistemic statement is a sentence automatically parsed. The classification is binary - epistemic statement or not. We will label epistemic statements only and one can assume that if a statement is not labeled, then it is not an epistemic statement.
The classifier is a CRF, trained on gold standard annotations of epistemic statements that are currently ongoing. We report an F-measure of 0.91 after 5-fold cross validation on a test set with 914 statements and an F-measure of 0.9 on a held out document with 130 statements. This project is still under development and is submitted to be used for the CovidLit project and associated Hackathon.
Please contact Mayla if you have any questions. | 1.42 M | | mboguslav | 2023-11-24 | Developing | |
biomarkers | | IL/TNF biomarkers | 857 K | | alo33 | 2023-11-24 | | |
Covid19_manual_annotation_v2 | | | 4.58 K | | AikoHIRAKI | 2023-11-24 | Developing | |
PubMed-German-test | | A collection of PubMed abstracts which are written in German | 0 | | Jin-Dong Kim | 2023-11-24 | Developing | |
PubMed-2017 | | abstracts published in 2017. | 0 | | Jin-Dong Kim | 2023-11-24 | Developing | |
speech-test | | | 6 | | Jin-Dong Kim | 2023-11-26 | Testing | |
ENG_NER_NEL | | Annotations in COVID-19 related PubMed abstracts from the following ontologies: Disease Ontology ("do"), Gene Ontology ("go"), Human Phenotype Ontology ("hpo"), ChEBI ontology ("chebi"), MeSH
| 493 | LASIGE-DeST | pruas_18 | 2023-11-26 | Developing | |
CORD-19-SciBite-sentences | | | 11.2 K | | Jin-Dong Kim | 2023-11-26 | Testing | |
FSU-PRGE | | A new broad-coverage corpus composed of 3,306 MEDLINE abstracts dealing with gene and protein mentions.
The annotation process was semi-automatic.
Publication: http://aclweb.org/anthology/W/W10/W10-1838.pdf | 59.5 K | CALBC Project | Yue Wang | 2023-11-26 | Released | |
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 | |
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 | |