pqqtest_sentence | | | 565 K | | yaoxinzhi | 2023-11-29 | Testing | |
GlyCosmos6-UBERON | | | 689 K | | Jin-Dong Kim | 2023-12-15 | Developing | |
PubMed_ArguminSci | | Predictions for PubMed automatically extracted with the ArguminSci tool (https://github.com/anlausch/ArguminSci). | 777 K | | zebet | 2023-11-24 | Released | |
0_colil | | | 781 K | | Yue Wang | 2023-11-24 | | |
biomarkers | | IL/TNF biomarkers | 857 K | | alo33 | 2023-11-24 | | |
UBERON-AE | | Annotation for anatomical entities based on the "Anatomical Entity" subtree of UBERON ontology.
Annotations are automatically produced using PubDictionaries with threshold: 0.85. | 859 K | DBCLS | Jin-Dong Kim | 2023-11-29 | Developing | |
PubCasesORDO | | ORDO annotation in PubCases | 865 K | | Toyofumi Fujiwara | 2023-11-24 | Beta | |
Biotea | | NCBO annotation on full text for PMC articles. Currently including only a small set of 2811 articles corresponding to those supporting curated diesease-protein annotation from UniProt and with machine-processable full text. | 894 K | L. Garcia | | 2023-11-24 | Developing | |
LitCovid-PD-HP | | | 922 K | | Jin-Dong Kim | 2023-11-28 | Beta | |
OryzaGP_2021 | | Updating OryzaGP | 1.08 M | Pierre Larmande | larmande | 2023-11-28 | Developing | |
CORD-19-PD-HP | | PubDictionaries annotation for HP terms - updated at 2020-04-30
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. | 1.15 M | | Jin-Dong Kim | 2023-11-29 | Released | |
GlyCosmos6-CLO | | Automatic annotation by PC-CLO. | 1.18 M | | Jin-Dong Kim | 2023-11-24 | Developing | |
LitCovid-PD-FMA-UBERON | | | 1.3 M | | Jin-Dong Kim | 2023-11-28 | Developing | |
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 | |
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 | |
LitCovid-PD-CHEBI | | | 1.43 M | | Jin-Dong Kim | 2023-11-24 | Developing | |
DisGeNET5_gene_disease | | The file contains gene-disease associations obtained by text mining MEDLINE abstracts using the BeFree system including the gene and disease off sets. | 2.04 M | IBI Group | Yue Wang | 2023-11-24 | Released | |
NEUROSES | | This corpus is composed of PubMed articles containing cognitive enhancers and anti-depressants drug mentions. The selected sentences are automatically annotated using the NCBO Annotator with the Chemical Entities of Biological Interest (CHEBI) and Phenotypic Quality Ontology (PATO) ontologies, we also produced annotations using PhenoMiner ontology via a dictionary-based tagger. | 2.14 M | | nestoralvaro | 2023-11-24 | 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-PD-MONDO | | | 2.26 M | | Jin-Dong Kim | 2023-11-24 | | |