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NameTDescription# Ann.Author MaintainerUpdated_atStatus

461-480 / 592 show all
pmc-enju-pas Predicate-argument structure annotation produced by Enju. This data set is initially produced as a supporting resource for BioNLP-ST 2016 GE task. As so, it currently includes the 34 full paper articles that are in the benchmark data sets of GE 2016 task, reference data set (bionlp-st-ge-2016-reference) and test data set (bionlp-st-ge-2016-test), but will be extended to include more papers from the PubMed Central Open Access subset (PMCOA). 205 KDBCLSJin-Dong Kim2023-11-28Developing
bionlp-st-ge-2016-test It 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 Kim2023-11-29Released
bionlp-st-ge-2016-test-proteins Protein annotations to the benchmark test data set of the BioNLP-ST 2016 GE task. A participant of the GE task may import the documents and annotations of this project to his/her own project, to begin with producing event annotations. For more details, please refer to the benchmark test data set (bionlp-st-ge-2016-test). 4.34 KDBCLSJin-Dong Kim2023-11-27Released
ICD10 Annotation for disease names as defined in ICD101.6 KDBCLSJin-Dong Kim2023-11-29Developing
sentences Sentence segmentation annotation. Automatic annotation by TextSentencer.6.96 MDBCLSJin-Dong Kim2023-11-24Developing
GO-CC Annotation for cellular components as defined in the "Cellular Component" subtree of Gene Ontology17.6 KDBCLSJin-Dong Kim2023-11-30Developing
GO-BP Annotation for biological processes as defined in the "Biological Process" subset of Gene Ontology35.4 KDBCLSJin-Dong Kim2023-11-29Developing
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 KDBCLSToyofumi Fujiwara2023-11-28Testing
bionlp-st-ge-2016-coref Coreference annotation to the benchmark data set (reference and test) of BioNLP-ST 2016 GE task. For detailed information, please refer to the benchmark reference data set (bionlp-st-ge-2016-reference) and benchmark test data set (bionlp-st-ge-2016-test).853DBCLSJin-Dong Kim2024-06-17Released
GO-MF Annotation for molecular functions as defined in the "Molecular Function" subtree of Gene Ontology19.7 KDBCLSJin-Dong Kim2023-12-04Testing
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 KDBCLSJin-Dong Kim2023-11-29Beta
PGR-NEG Identification of Negative Relations 23Diana Sousadpavot2023-11-28Developing
PGR-UNK Identification of Unknown Relations 91Diana Sousadpavot2023-11-29Developing
PGR-FAL Identification of False Relations128Diana Sousadpavot2023-11-29Developing
ENG_RE Entities and relations annotations from the following ontologies: Disease Ontology ('DO'), Gene Ontology ('GO'), Human Phenotype Ontology ('HPO'), and ChEBI ontology ('CHEBI').224Diana Sousadpavot2023-11-29Developing
pubmed-enju-pas Annotating PubMed abstracts for predicate-argument structure (PAS). Enju 2.4.2 is used to automatically compute PAS.19.1 MEnjuJin-Dong Kim2023-11-24Developing
Erin_test @ Yonsei University0ErinErinHJ_Kim2023-11-29Testing
SPECIES800_autotagged This project comprises the SPECIES800 corpus documents automatically annotated by the Jensenlab tagger. Annotated entity types are: Genes/proteins from the mentioned organisms (and any human ones) PubChem Compound identifiers NCBI Taxonomy entries Gene Ontology cellular component terms BRENDA Tissue Ontology terms Disease Ontology terms Environment Ontology terms The SPECIES 800 (S800) comprises 800 PubMed abstracts. In its original form species mentions were manually 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.0065390. The manually annotated corpus is also available as a PubAnnotation project (see here). 0Evangelos Pafilis, Sampo Pyysalo, Lars Juhl Jensenevangelos2015-11-20Testing
SPECIES800 SPECIES 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 Jensenevangelos2023-11-28Released
2015-BEL-Sample An attempt to upload 295 BEL statements, i.e. the sample set used for the 2015 BioCreative challenge. 58Fabio RinaldiFabio Rinaldi2023-11-29Testing
NameT# Ann.Author MaintainerUpdated_atStatus

461-480 / 592 show all
pmc-enju-pas 205 KDBCLSJin-Dong Kim2023-11-28Developing
bionlp-st-ge-2016-test 7.99 KDBCLSJin-Dong Kim2023-11-29Released
bionlp-st-ge-2016-test-proteins 4.34 KDBCLSJin-Dong Kim2023-11-27Released
ICD10 1.6 KDBCLSJin-Dong Kim2023-11-29Developing
sentences 6.96 MDBCLSJin-Dong Kim2023-11-24Developing
GO-CC 17.6 KDBCLSJin-Dong Kim2023-11-30Developing
GO-BP 35.4 KDBCLSJin-Dong Kim2023-11-29Developing
Colil 3.34 KDBCLSToyofumi Fujiwara2023-11-28Testing
bionlp-st-ge-2016-coref 853DBCLSJin-Dong Kim2024-06-17Released
GO-MF 19.7 KDBCLSJin-Dong Kim2023-12-04Testing
bionlp-st-ge-2016-uniprot 16.2 KDBCLSJin-Dong Kim2023-11-29Beta
PGR-NEG 23Diana Sousadpavot2023-11-28Developing
PGR-UNK 91Diana Sousadpavot2023-11-29Developing
PGR-FAL 128Diana Sousadpavot2023-11-29Developing
ENG_RE 224Diana Sousadpavot2023-11-29Developing
pubmed-enju-pas 19.1 MEnjuJin-Dong Kim2023-11-24Developing
Erin_test 0ErinErinHJ_Kim2023-11-29Testing
SPECIES800_autotagged 0Evangelos Pafilis, Sampo Pyysalo, Lars Juhl Jensenevangelos2015-11-20Testing
SPECIES800 3.71 KEvangelos Pafilis, Sune P. Frankild, Lucia Fanini, Sarah Faulwetter, Christina Pavloudi, Aikaterini Vasileiadou, Christos Arvanitidis, Lars Juhl Jensenevangelos2023-11-28Released
2015-BEL-Sample 58Fabio RinaldiFabio Rinaldi2023-11-29Testing