| 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/W12-2430 | 1.1 K | 2016-05-17 | Released | |
| bionlp-st-cg-2013-training | | The training dataset from the cancer genetics task in the BioNLP Shared Task 2013.
Composed of anatomical and molecular entities. | 10.9 K | 2016-12-06 | Released | |
| AIMed | | The AIMed corpus is one of the most widely used corpora for protein-protein interaction extraction. The protein annotations are either parts of the protein interaction annotations, or are uninvolved in any protein interaction annotation.
Publication: http://www.cs.utexas.edu/~ml/papers/bionlp-aimed-04.pdf | 4.04 K | 2017-04-14 | Testing | |
| 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 K | 2017-08-28 | Released | |
| bionlp-st-bb3-2016-training | | Entity (bacteria, habitats and geographical places) annotation to the training dataset of the BioNLP-ST 2016 BB task.
For more information, please refer to bionlp-st-bb3-2016-development and bionlp-st-bb3-2016-test.
Bacteria
Bacteria entities are annotated as contiguous spans of text that contains a full unambiguous prokaryote taxon name, the type label is Bacteria. The Bacteria type is a taxon, at any taxonomic level from phylum (Eubacteria) to strain. The category that the text entities have to be assigned to is the most specific and unique category of the NCBI taxonomy resource. In case a given strain, or a group of strains is not referenced by NCBI, it is assigned with the closest taxid in the taxonomy.
Habitat
Habitat entities are annotated as spans of text that contains a complete mention of a potential habitat for bacteria, the type label is Habitat. Habitat entities are assigned one or several concepts from the habitat subpart of the OntoBiotope ontology. The assigned concepts are as specific as possible. OntoBiotope defines most relevant microorganism habitats from all areas considered by microbial ecology (hosts, natural environment, anthropized environments, food, medical, etc.). Habitat entities are rarely referential entities, they are usually noun phrases including properties and modifiers. There are rare cases of habitats referred with adjectives or verbs. The spans are generally contiguous but some of them are discontinuous in order to cope with conjunctions.
Geographical
Geographical entities are geographical and organization places denoted by official names. | 1.29 K | 2017-05-22 | Released | |
| 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.pdf | 59.5 K | 2017-03-08 | Released | |
| PIR-corpus2 | | The protein tag was used to tag proteins, or protein-associated or -related objects, such as domains, pathways, expression of gene.
Annotation guideline: http://pir.georgetown.edu/pirwww/about/doc/manietal.pdf | 5.52 K | 2020-02-01 | Released | |
| bionlp-st-epi-2011-training | | The training dataset from the Epigenetics and Post-translational Modifications (EPI) task in the BioNLP Shared Task 2011.
The core entities of the task are genes and gene products (RNA and proteins), identified in the data simply as "Protein" annotations. | 7.6 K | 2016-12-06 | Released | |
| SCAI-Test | | A small corpus for the evaluation of dictionaries containing chemical entities.
Publication: http://www.scai.fraunhofer.de/fileadmin/images/bio/data_mining/paper/kolarik2008.pdf
Original source: https://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads/corpora-for-chemical-entity-recognition.html | 1.21 K | 2017-04-03 | Released | |
| 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 | 2020-02-02 | Released | |
