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NameTDescription# Ann.AuthorMaintainerUpdated_atStatus

1-20 / 272 show all
AGAC_training3.32 Kxiajingbo2019-09-12Released
AGAC_test0xiajingbo2019-07-12Released
AGAC_sample874xiajingbo2019-06-30Released
GlyCosmos600-docsA random collection of 600 PubMed abstracts from 6 glycobiology-related journals: Glycobiology, Glycoconjugate journal, The Journal of biological chemistry, Journal of proteome research, Journal of proteomics, and Carbohydrate research. The whole PMIDs were collected on June 11, 2019. From each journal, 100 PMIDs were randomly sampled.0Jin-Dong Kim2019-06-11Released
bionlp-st-ge-2016-testIt is the benchmark test data set of the BioNLP-ST 2016 GE task. It includes Genia-style event annotations to 14 full paper articles which are about NFκB proteins. For testing purpose, however, annotations are all blinded, which means users cannot see the annotations in this project. Instead, annotations in any other project can be compared to the hidden annotations in this project, then the annotations in the project will be automatically evaluated based on the comparison. A participant of GE task can get the evaluation of his/her result of automatic annotation, through following process: Create a new project. Import documents from the project, bionlp-st-2016-test-proteins to your project. Import annotations from the project, bionlp-st-2016-test-proteins to your project. At this point, you may want to compare you project to this project, the benchmark data set. It will show that protein annotations in your project is 100% correct, but other annotations, e.g., events, are 0%. Produce event annotations, using your system, upon the protein annotations. Upload your event annotations to your project. Compare your project to this project, to get evaluation. GE 2016 benchmark data set is provided as multi-layer annotations which include: bionlp-st-ge-2016-reference: benchmark reference data set bionlp-st-ge-2016-test: benchmark test data set (this project) bionlp-st-ge-2016-test-proteins: protein annotation to the benchmark test data set Following is supporting resources: bionlp-st-ge-2016-coref: coreference annotation bionlp-st-ge-2016-uniprot: Protein annotation with UniProt IDs. pmc-enju-pas: dependency parsing result produced by Enju UBERON-AE: annotation for anatomical entities as defined in UBERON ICD10: annotation for disease names as defined in ICD10 GO-BP: annotation for biological process names as defined in GO GO-CC: annotation for cellular component names as defined in GO A SPARQL-driven search interface is provided at http://bionlp.dbcls.jp/sparql.7.99 KDBCLSJin-Dong Kim2019-04-30Released
123123123123123123150yaoxinzhi2019-04-12Released
craft-sa-devDevelopment 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.512 KUniversity of Colorado Anschutz Medical Campuscraft-st2019-03-25Released
craft-ca-core-ex-devDevelopment data for CRAFT CA shared task, core concepts + EXTENSIONS. This project contains the development (training) annotations for the Concept Annotation task of the CRAFT Shared Task 2019. This particular set of concept annotations is the "core+extensions" set. See the task description for details, but this set contains annotations to concepts that appear in the original 10 Open Biomedical Ontologies used for annotation PLUS annotations to extension classes created using the core concepts.94.3 KUniversity of Colorado Anschutz Medical Campuscraft-st2019-03-25Released
craft-ca-core-devDevelopment data for CRAFT CA shared task, core concepts only. This project contains the development (training) annotations for the Concept Annotation task of the CRAFT Shared Task 2019. This particular set of concept annotations is the "core" set. See the task description for details, but this set contains only annotations to concepts that appear in the original 10 Open Biomedical Ontologies used for annotation. (That is to say, it does not contain any annotations to extension classes).62.3 KUniversity of Colorado Anschutz Medical Campuscraft-st2019-03-25Released
RDoCTask1SampleDataEach annotation file contains an annotated abstract with an RDoC category. Each title span in these sample data is annotated with the corresponding related RDoC construct, although the RDoC category would apply for the entire abstract. The annotation data are formatted as json files. Please refer to the following page for a more detailed description of the json format http://www.pubannotation.org/docs/annotation-format/.20mmanani1s2019-03-25Released
RDoCTask2SampleDataEach annotation file contains an annotated abstract with the most relevant sentence. The relevant sentence is annotated with the RDoC category name. The annotation data are formatted as json files. Please refer to the following page for a more detailed description of the json format http://www.pubannotation.org/docs/annotation-format/. 10mmanani1s2019-03-25Released
spacy-testRandom set of articles used for testing in the development of the RESTful spaCy parsing web service. Since development is now finished, they are released for the community to use.137 KNico ColicNico Colic2019-03-16Released
DisGeNET5_gene_diseaseThe 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 Wang2019-01-17Released
DisGeNET5_variant_diseaseThe 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 Wang2019-01-09Released
GENIAcorpus multi_cell (1,782) mono_cell (222) virus (2,136) protein_family_or_group (8,002) protein_complex (2,394) protein_molecule (21,290) protein_subunit (942) protein_substructure (129) protein_domain_or_region (1,044) protein_other (97) peptide (521) amino_acid_monomer (784) DNA_family_or_group (332) DNA_molecule (664) DNA_substructure (2) DNA_domain_or_region (39) DNA_other (16) RNA_family_or_group (1,545) RNA_molecule (554) RNA_substructure (106) RNA_domain_or_region (8,237) RNA_other (48) polynucleotide (259) nucleotide (243) lipid (2,375) carbohydrate (99) other_organic_compound (4,113) body_part (461) tissue (706) cell_type (7,473) cell_component (679) cell_line (4,129) other_artificial_source (211) inorganic (258) atom (342) other (21,056) 79.2 KGENIA ProjectYue Wang2018-08-22Released
SPECIES800SPECIES 800 (S800): an abstract-based manually annotated corpus. S800 comprises 800 PubMed abstracts in which organism mentions were identified and mapped to the corresponding NCBI Taxonomy identifiers. Described in: The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text. Pafilis E, Frankild SP, Fanini L, Faulwetter S, Pavloudi C, et al. (2013). PLoS ONE, 2013, 8(6): e65390. doi:10.1371/journal.pone.00653903.71 KEvangelos Pafilis, Sune P. Frankild, Lucia Fanini, Sarah Faulwetter, Christina Pavloudi, Aikaterini Vasileiadou, Christos Arvanitidis, Lars Juhl Jensenevangelos2018-04-25Released
WangshuguangHZAU_bioinformatics_competition603wangshuguangwangshuguang2018-04-03Released
bionlp-st-2016-SeeDev-testEntities annotations from the test set of the BioNLP-ST 2016 SeeDev task. SeeDev task focuses on seed storage and reserve accumulation on the model organism, Arabidopsis thaliana. The SeeDev task is based on the knowledge model Gene Regulation Network for Arabidopsis (GRNA) that meets the needs of text-mining (i.e. manual annotation of texts and automatic information extraction), experimental data indexing and retrieval and reuse in other plant systems. It is also expected to meet the requirements of the integration of the text knowledge with knowledge derived from experimental data in view of modeling in systems biology. GRNA model defines 16 different types of entities, and 22 types of event (in five sets of event types) that may be combined in complex events. For more information, please refer to the task website All annotations : Train set Development set Test set (without events) 184EstelleChaix2018-01-13Released
bionlp-st-2016-SeeDev-trainingEntities and event annotations from the training set of the BioNLP-ST 2016 SeeDev task. SeeDev task focuses on seed storage and reserve accumulation on the model organism, Arabidopsis thaliana. The SeeDev task is based on the knowledge model Gene Regulation Network for Arabidopsis (GRNA) that meets the needs of text-mining (i.e. manual annotation of texts and automatic information extraction), experimental data indexing and retrieval and reuse in other plant systems. It is also expected to meet the requirements of the integration of the text knowledge with knowledge derived from experimental data in view of modeling in systems biology. GRNA model defines 16 different types of entities, and 22 types of event (in five sets of event types) that may be combined in complex events. For more information, please refer to the task website All annotations : Train set Development set Test set (without events) 35EstelleChaix2018-01-13Released
bionlp-st-2016-SeeDev-devEntities and event annotations from the development set of the BioNLP-ST 2016 SeeDev task. SeeDev task focuses on seed storage and reserve accumulation on the model organism, Arabidopsis thaliana. The SeeDev task is based on the knowledge model Gene Regulation Network for Arabidopsis (GRNA) that meets the needs of text-mining (i.e. manual annotation of texts and automatic information extraction), experimental data indexing and retrieval and reuse in other plant systems. It is also expected to meet the requirements of the integration of the text knowledge with knowledge derived from experimental data in view of modeling in systems biology. GRNA model defines 16 different types of entities, and 22 types of event (in five sets of event types) that may be combined in complex events. For more information, please refer to the task website All annotations : Train set Development set Test set (without events) 61EstelleChaix2018-01-13Released
NameT# Ann.AuthorMaintainerUpdated_atStatus

1-20 / 272 show all
AGAC_training3.32 Kxiajingbo2019-09-12Released
AGAC_test0xiajingbo2019-07-12Released
AGAC_sample874xiajingbo2019-06-30Released
GlyCosmos600-docs0Jin-Dong Kim2019-06-11Released
bionlp-st-ge-2016-test7.99 KDBCLSJin-Dong Kim2019-04-30Released
123123123150yaoxinzhi2019-04-12Released
craft-sa-dev512 KUniversity of Colorado Anschutz Medical Campuscraft-st2019-03-25Released
craft-ca-core-ex-dev94.3 KUniversity of Colorado Anschutz Medical Campuscraft-st2019-03-25Released
craft-ca-core-dev62.3 KUniversity of Colorado Anschutz Medical Campuscraft-st2019-03-25Released
RDoCTask1SampleData20mmanani1s2019-03-25Released
RDoCTask2SampleData10mmanani1s2019-03-25Released
spacy-test137 KNico ColicNico Colic2019-03-16Released
DisGeNET5_gene_disease2.04 MIBI GroupYue Wang2019-01-17Released
DisGeNET5_variant_disease144 KIBI GroupYue Wang2019-01-09Released
GENIAcorpus79.2 KGENIA ProjectYue Wang2018-08-22Released
SPECIES8003.71 KEvangelos Pafilis, Sune P. Frankild, Lucia Fanini, Sarah Faulwetter, Christina Pavloudi, Aikaterini Vasileiadou, Christos Arvanitidis, Lars Juhl Jensenevangelos2018-04-25Released
Wangshuguang603wangshuguangwangshuguang2018-04-03Released
bionlp-st-2016-SeeDev-test184EstelleChaix2018-01-13Released
bionlp-st-2016-SeeDev-training35EstelleChaix2018-01-13Released
bionlp-st-2016-SeeDev-dev61EstelleChaix2018-01-13Released