| 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 | 2020-04-30 | Released | |
| LitCovid-PD-FMA-UBERON | | 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. | 4.29 K | | Jin-Dong Kim | 2020-05-10 | Released | |
| LitCovid-PD-MONDO | | PubDictionaries annotation for disease terms - updated at 2020-04-20
It is based on MONDO Version 2020-04-20.
The terms in MONDO 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. | 13.4 K | | Jin-Dong Kim | 2020-05-10 | Released | |
| 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 | 2020-05-12 | Released | |
| LitCovid-PD-HP | | PubDictionaries annotation for human phenotype terms - updated at 2020-04-20
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. | 3.02 K | | Jin-Dong Kim | 2020-05-25 | Released | |
| LitCovid-OGER-BB | | Using OGER (www.ontogene.com) and Biobert to obtain annotations for 10 different vocabularies. | 223 K | Fabio Rinaldi | Nico Colic | 2020-06-04 | Released | |
| DisGeNET | | Disease-Gene association annotation. | 3.12 M | Nuria Queralt | Jin-Dong Kim | 2016-01-28 | Beta | |
| 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. | 2.15 M | | nestoralvaro | 2016-02-24 | Beta | |
| 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 | 2016-05-22 | Beta | |
| PubCasesHPO | | HPO annotation in PubCases | 3.2 M | | Toyofumi Fujiwara | 2017-09-06 | Beta | |
| PubCasesORDO | | ORDO annotation in PubCases | 869 K | | Toyofumi Fujiwara | 2017-09-14 | Beta | |
| LitCovid-PAS-Enju | | Predicate-argument structure annotation produced by the Enju parser. | 125 K | | Jin-Dong Kim | 2020-03-25 | Beta | |
| PubmedHPO | | Human phenotype annotation to PubMed abstracts, based on the HPO ontology | 12.4 M | Tudor Groza | tudor | 2020-04-01 | Beta | |
| IMDB-NLP | | Annotations for chunking and semantic role labeling based on in-memory databases. | 0 | | | 2016-05-06 | Uploading | |
| OryzaGP | | A dataset for Named Entity Recognition for rice gene | 29.1 K | Huy Do and Pierre Larmande | Yue Wang | 2019-03-13 | Uploading | |
| relna | | https://www.tagtog.net/jmcejuela/relna | 2.77 K | Ashish Baghudana and Juan Miguel Cejuela | tagtog | 2015-11-25 | Developing | |
| uniprot-mouse | | Protein annotation based on UniProt | 11.5 K | | Jin-Dong Kim | 2016-04-27 | Developing | |
| ICD10 | | Annotation for disease names as defined in ICD10 | 1.6 K | DBCLS | Jin-Dong Kim | 2016-05-04 | Developing | |
| tees-test | | Random PMC document used for testing during the development of a RESTful TEES parsing web service. | 467 | Nico Colic | Nico Colic | 2016-05-25 | Developing | |
| PubMed-2017 | | abstracts published in 2017. | 0 | | Jin-Dong Kim | 2017-09-01 | Developing | |
