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NameT Description# Ann.AuthorMaintainerUpdated_atStatus

581-600 / 601 show all
LitCovid-PD-UBERON 540 KJin-Dong Kim2023-11-29
LitCovid-PD-MONDO 2.26 MJin-Dong Kim2023-11-24
MicrobeTaxon 1.23 KYo Shidahara2023-11-26Testing
test1 test121H. S. ParkSophie Nam2023-11-26Testing
2015-BEL-Sample-2 The 295 BEL statements for sample set used for the 2015 BioCreative challenge.11.4 KFabio RinaldiNico Colic2023-11-28Released
BioLarkPubmedHPO 228 abstracts manually annotated with Human Phenotype Ontology (HPO) concepts and harmonized by three curators, which can be used as a reference standard for free text annotation of human phenotypes. For more info, please see Groza et al. "Automatic concept recognition using the human phenotype ontology reference and test suite corpora", 2015.7.16 KTudor Grozasimon2023-11-29Released
GO-CC Annotation for cellular components as defined in the "Cellular Component" subtree of Gene Ontology17.6 KDBCLSJin-Dong Kim2023-11-30Developing
PGDBj_disease_curation1 disease curation test348ichihara_hisakoichihara_hisako2023-12-03Testing
CellFinder CellFinder corpus4.75 KMariana Neves, Alexander Damaschun, Andreas Kurtz, Ulf LeserMariana Neves2023-11-27Released
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 KNaCTeMYue Wang2023-11-28Released
WikiPainGoldStandard Wiki-pain contains molecular interactions that are relevant to pain.878Daniel Jamiesonnikolamilosevic2023-11-28Developing
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
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
testone 6.76 Kykyao2023-11-29
GO-BP Annotation for biological processes as defined in the "Biological Process" subset of Gene Ontology35.4 KDBCLSJin-Dong Kim2023-11-29Developing
simple1 4.34 Khxr-2016_dlut2023-11-29
test3 10.7 Kykyao2023-11-29
BLAH2015_Annotations_test_5 1.34 Knestoralvaronestoralvaro2023-11-30Testing
GO-MF Annotation for molecular functions as defined in the "Molecular Function" subtree of Gene Ontology19.7 KDBCLSJin-Dong Kim2023-12-04Testing
DLUT931 DLUT NLP Lab.Test our event extration result for 16 GE task.4.57 KDLUT9312023-11-30Testing
NameT # Ann.AuthorMaintainerUpdated_atStatus

581-600 / 601 show all
LitCovid-PD-UBERON 540 KJin-Dong Kim2023-11-29
LitCovid-PD-MONDO 2.26 MJin-Dong Kim2023-11-24
MicrobeTaxon 1.23 KYo Shidahara2023-11-26Testing
test1 21H. S. ParkSophie Nam2023-11-26Testing
2015-BEL-Sample-2 11.4 KFabio RinaldiNico Colic2023-11-28Released
BioLarkPubmedHPO 7.16 KTudor Grozasimon2023-11-29Released
GO-CC 17.6 KDBCLSJin-Dong Kim2023-11-30Developing
PGDBj_disease_curation1 348ichihara_hisakoichihara_hisako2023-12-03Testing
CellFinder 4.75 KMariana Neves, Alexander Damaschun, Andreas Kurtz, Ulf LeserMariana Neves2023-11-27Released
bionlp-st-cg-2013-training 10.9 KNaCTeMYue Wang2023-11-28Released
WikiPainGoldStandard 878Daniel Jamiesonnikolamilosevic2023-11-28Developing
tmVarCorpus 1.43 KChih-Hsuan Wei , Bethany R. Harris , Hung-Yu Kao and Zhiyong LuChih-Hsuan Wei2023-11-24Released
bionlp-st-ge-2016-test 7.99 KDBCLSJin-Dong Kim2023-11-29Released
testone 6.76 Kykyao2023-11-29
GO-BP 35.4 KDBCLSJin-Dong Kim2023-11-29Developing
simple1 4.34 Khxr-2016_dlut2023-11-29
test3 10.7 Kykyao2023-11-29
BLAH2015_Annotations_test_5 1.34 Knestoralvaronestoralvaro2023-11-30Testing
GO-MF 19.7 KDBCLSJin-Dong Kim2023-12-04Testing
DLUT931 4.57 KDLUT9312023-11-30Testing