| CORD-19-sample-sentences | | | 161 | | Jin-Dong Kim | 2023-11-27 | Developing | |
| CORD-19-sample-paragraphs | | | 28 | | Jin-Dong Kim | 2023-11-29 | Developing | |
| CORD-19-sample-MONDO | | | 113 | | Jin-Dong Kim | 2023-11-29 | Developing | |
| CORD-19-sample-IDO | | | 76 | | Jin-Dong Kim | 2023-11-29 | Developing | |
| CORD-19-sample-HP | | | 39 | | Jin-Dong Kim | 2023-11-27 | Developing | |
| CORD-19-sample-FMA-UBERON | | | 61 | | Jin-Dong Kim | 2023-11-29 | Developing | |
| CORD-19-sample-CHEBI | | | 16 | | Jin-Dong Kim | 2023-11-29 | 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 | |
| CORD-19-PD-MONDO | | PubDictionaries annotation for MONDO terms - updated at 2020-04-30
It is disease term annotation 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. | 6.32 M | | Jin-Dong Kim | 2023-11-27 | 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 | 2023-11-29 | Released | |
| CORD-19_Non-commercial_use_subset | | The Non commercial use 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. | 0 | | Jin-Dong Kim | 2023-11-29 | Released | |
| CORD-19_HIRAKI | | HIRAKI Annotation for CORD-19 | 2.98 K | | AikoHIRAKI | 2023-11-29 | Testing | |
| 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 | |
| CORD-19_Commercial_use_subset | | The Commercial use 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. | 0 | | Jin-Dong Kim | 2023-11-29 | Released | |
| CORD-19_bioRxiv_medRxiv_subset | | The bioRxiv/medRxiv subset of the CORD-19 dataset: pre-prints that are not peer reviewed.
The documents in this project will be updated as the CORD-19 dataset grows.
See the COVID DATASET LICENSE AGREEMENT.
| 0 | | Jin-Dong Kim | 2023-11-29 | Released | |
| CORD-19_All_docs | | All the documents in the whole CORD-19 dataset.
The documents in this project will be updated as the CORD-19 dataset grows.
See the COVID DATASET LICENSE AGREEMENT. | 0 | | Jin-Dong Kim | 2023-11-29 | Released | |
| consensus_PMA_Age_Indications | | | 1.7 K | | laurenc | 2023-11-28 | Beta | |
| Computational_Biology | | | 0 | | Sophie Nam | 2023-11-29 | | |
| CoMAGC | | In order to access the large amount of information in biomedical literature about genes implicated in various cancers both efficiently and accurately, the aid of text mining (TM) systems is invaluable. Current TM systems do target either gene-cancer relations or biological processes involving genes and cancers, but the former type produces information not comprehensive enough to explain how a gene affects a cancer, and the latter does not provide a concise summary of gene-cancer relations. In order to support the development of TM systems that are specifically targeting gene-cancer relations but are still able to capture complex information in biomedical sentences, we publish CoMAGC, a corpus with multi- faceted annotations of gene-cancer relations. In CoMAGC, a piece of annotation is composed of four semantically orthogonal concepts that together express 1) how a gene changes, 2) how a cancer changes and 3) the causality between the gene and the cancer. The multi-faceted annotations are shown to have high inter-annotator agreement. In addition, the annotations in CoMAGC allow us to infer the prospective roles of genes in cancers and to classify the genes into three classes according to the inferred roles. We encode the mapping between multi-faceted annotations and gene classes into 10 inference rules. The inference rules produce results with high accuracy as measured against human annotations. CoMAGC consists of 821 sentences on prostate, breast and ovarian cancers. Currently, the corpus deals with changes in gene expression levels among other types of gene changes. | 1.53 K | Lee et al | Hee-Jin Lee | 2023-11-24 | Released | |
| Colil | | Colil (Comments on Literature in Literature) is a search service for citation contexts utilized in the biomedical domain. Colil searches for a cited paper in the Colil database and then returns a list of the citation contexts for it and its relevant papers based on co-citations. | 3.34 K | DBCLS | Toyofumi Fujiwara | 2023-11-28 | Testing | |
