| 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 | |
| test10 | | | 212 | | Jin-Dong Kim | 2023-11-24 | | |
| 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 | |
| proj_h_1 | | | 6.7 K | | | 2023-11-24 | | |
| 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 | |
| CORD-19-SciBite-sentences | | | 11.2 K | | Jin-Dong Kim | 2023-11-26 | Testing | |
| 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 | |
| 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 | |
| disease_gene_microbe_small | | Small version (48 abstract that mention both Crohns and S. aureus) for development purposes
Abbreviation: dgm Content: annotated abstracts on Crohn’s disease or on on Staphylococcus aureus (according to the jensenlab.org indexing resources) Entity types: (three for a start, organisms (NCBI Taxonomy taxa), disease (Disease Ontology terms), human genes (ENSEMBL proteins) Aim: Explore indirect associations of diseases to microbial species in this corpus via gene co-mentions | 536 | | evangelos | 2023-11-27 | Testing | |
| consensus_PMA_Age_Indications | | | 1.7 K | | laurenc | 2023-11-28 | Beta | |
| 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 | |
| LitCovid-ArguminSci | | Discourse elements for the documents in the LitCovid dataset.
Annotations were automatically predicted by the ArguminSci tool (https://github.com/anlausch/ArguminSci) | 4.9 K | | zebet | 2023-11-27 | Released | |
| GlyCosmos6-Glycan-Image | | | 1.95 K | | Jin-Dong Kim | 2024-05-17 | Developing | |
| bionlp-st-2016-SeeDev-training | | Entities and event annotations from the training set of the BioNLP-ST 2016 SeeDev task.
SeeDev task focuses on seed storage and reserve accumulation on the model organism, Arabidopsis thaliana. The SeeDev task is based on the knowledge model Gene Regulation Network for Arabidopsis (GRNA) that meets the needs of text-mining (i.e. manual annotation of texts and automatic information extraction), experimental data indexing and retrieval and reuse in other plant systems. It is also expected to meet the requirements of the integration of the text knowledge with knowledge derived from experimental data in view of modeling in systems biology.
GRNA model defines 16 different types of entities, and 22 types of event (in five sets of event types) that may be combined in complex events.
For more information, please refer to the task website
All annotations :
Train set
Development set
Test set (without events)
| 35 | | EstelleChaix | 2023-11-28 | Released | |
