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NameTDescription# Ann.AuthorMaintainerUpdated_atStatus

1-20 / 556 show all
Virus300 300 abstracts from virology journals annotated with viral proteins and species0http://aclweb.org/anthology/W/W17/W17-2311.pdfhelencook2017-08-07Released
geneset_names 0alo332022-04-26Released
Inflammaging Inflammation axis23.4 Malo332023-11-24Released
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 MJin-Dong Kim2023-11-24Released
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 MIBI GroupYue Wang2023-11-24Released
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 MJin-Dong Kim2023-11-24Released
PubMed_ArguminSci Predictions for PubMed automatically extracted with the ArguminSci tool (https://github.com/anlausch/ArguminSci).777 Kzebet2023-11-24Released
tmVarCorpus Wei C-H, Harris BR, Kao H-Y, Lu Z (2013) tmVar: A text mining approach for extracting sequence variants in biomedical literature, Bioinformatics, 29(11) 1433-1439, doi:10.1093/bioinformatics/btt156.1.43 KChih-Hsuan Wei , Bethany R. Harris , Hung-Yu Kao and Zhiyong LuChih-Hsuan Wei2023-11-24Released
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 KLee et alHee-Jin Lee2023-11-24Released
DisGeNET5_variant_disease The file contains variant-disease associations obtained by text mining MEDLINE abstracts using the BeFree system, including the variant and disease off sets. 144 KIBI GroupYue Wang2023-11-24Released
jnlpba-st-training The training data used in the task came from the GENIA version 3.02 corpus, This was formed from a controlled search on MEDLINE using the MeSH terms "human", "blood cells" and "transcription factors". From this search, 1,999 abstracts were selected and hand annotated according to a small taxonomy of 48 classes based on a chemical classification. Among the classes, 36 terminal classes were used to annotate the GENIA corpus. For the shared task only the classes protein, DNA, RNA, cell line and cell type were used. The first three incorporate several subclasses from the original taxonomy while the last two are interesting in order to make the task realistic for post-processing by a potential template filling application. The publication year of the training set ranges over 1990~1999.51.1 KGENIAYue Wang2023-11-26Released
CyanoBase Cyanobacteria are prokaryotic organisms that have served as important model organisms for studying oxygenic photosynthesis and have played a significant role in the Earthfs history as primary producers of atmospheric oxygen. Publication: http://www.aclweb.org/anthology/W12-24301.1 KKazusa DNA Research Institute and Database Center for Life Science (DBCLS)Yue Wang2023-11-26Released
PennBioIE The PennBioIE corpus (0.9) covers two domains of biomedical knowledge. One is the inhibition of the cytochrome P450 family of enzymes (CYP450 or CYP for short) , and the other domain is the molecular genetics of dance (oncology or onco for short).23.8 KUPenn Biomedical Information Extraction ProjectYue Wang2023-11-26Released
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.pdf59.5 KCALBC ProjectYue Wang2023-11-26Released
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 MJin-Dong Kim2023-11-27Released
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 KJin-Dong Kim2023-11-27Released
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 Kzebet2023-11-27Released
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 Kzebet2023-11-27Released
craft-sa-dev Development data for CRAFT SA shared task. This project contains the development (training) annotations for the Structural Annotation task of the CRAFT Shared Task 2019. This particular set contains token and sentence annotations with tokens linked via dependency relations. These dependency relations were automatically generated using the manually curated CRAFT constituency treebank files as input.490 KUniversity of Colorado Anschutz Medical Campuscraft-st2023-11-27Released
bionlp-st-pc-2013-training The training dataset from the pathway curation (PC) task in the BioNLP Shared Task 2013. The entity types defined in the PC task are simple chemical, gene or gene product, complex and cellular component.7.86 KNaCTeM and KISTIYue Wang2023-11-27Released
NameT# Ann.AuthorMaintainerUpdated_atStatus

1-20 / 556 show all
Virus300 0http://aclweb.org/anthology/W/W17/W17-2311.pdfhelencook2017-08-07Released
geneset_names 0alo332022-04-26Released
Inflammaging 23.4 Malo332023-11-24Released
CORD-19_Custom_license_subset 5.08 MJin-Dong Kim2023-11-24Released
DisGeNET5_gene_disease 2.04 MIBI GroupYue Wang2023-11-24Released
CORD-19-PD-UBERON 1.42 MJin-Dong Kim2023-11-24Released
PubMed_ArguminSci 777 Kzebet2023-11-24Released
tmVarCorpus 1.43 KChih-Hsuan Wei , Bethany R. Harris , Hung-Yu Kao and Zhiyong LuChih-Hsuan Wei2023-11-24Released
CoMAGC 1.53 KLee et alHee-Jin Lee2023-11-24Released
DisGeNET5_variant_disease 144 KIBI GroupYue Wang2023-11-24Released
jnlpba-st-training 51.1 KGENIAYue Wang2023-11-26Released
CyanoBase 1.1 KKazusa DNA Research Institute and Database Center for Life Science (DBCLS)Yue Wang2023-11-26Released
PennBioIE 23.8 KUPenn Biomedical Information Extraction ProjectYue Wang2023-11-26Released
FSU-PRGE 59.5 KCALBC ProjectYue Wang2023-11-26Released
CORD-19-PD-MONDO 6.32 MJin-Dong Kim2023-11-27Released
LitCovid-PD-FMA-UBERON-v1 4.3 KJin-Dong Kim2023-11-27Released
LitCovid-ArguminSci 4.9 Kzebet2023-11-27Released
LitCovid-PubTatorCentral 4.64 Kzebet2023-11-27Released
craft-sa-dev 490 KUniversity of Colorado Anschutz Medical Campuscraft-st2023-11-27Released
bionlp-st-pc-2013-training 7.86 KNaCTeM and KISTIYue Wang2023-11-27Released