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Name TDescription# Ann.AuthorMaintainerUpdated_atStatus

1-20 / 160 show all
2015-BEL-SampleAn attempt to upload 295 BEL statements, i.e. the sample set used for the 2015 BioCreative challenge. 58Fabio RinaldiFabio Rinaldi2015-02-26Testing
2015-BEL-Sample-2The 295 BEL statements for sample set used for the 2015 BioCreative challenge.11.4 KFabio RinaldiNico Colic2016-05-25Released
Ab3P-abbreviationsThis corpus was developed during the creation of the Ab3P abbreviation definition identification tool. It includes 1250 manually annotated MEDLINE records. This gold standard includes 1221 abbreviation-definition pairs. Abbreviation definition identification based on automatic precision estimates Sunghwan Sohn, Donald C Comeau, Won Kim and W John Wilbur BMC Bioinformatics20089:402 DOI: 10.1186/1471-2105-9-4022.34 KSunghwan Sohn, Donald C Comeau, Won Kim and W John Wilburcomeau2016-07-29Beta
AIMedThe 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.pdf4.04 KThe University of Texas at AustinYue Wang2017-04-14Testing
AllieAn annotation set of abbreviations and expanded forms extracted from PubMed/MEDLINE by machines.8.7 MDatabase Center for Life ScienceYasunori Yamamoto2017-04-06Developing
Alvis4PubannotationThis project contains corpus that are used with the customized annotator of AlvisNLP. 0Ba2017-01-17Testing
AlvisNLP-Async-TestTest for the asynchronous AlvisNLP/ML annotator family.0Robert Bossyrbossy2017-04-07Testing
AlvisNLP-TestProject for testing AlviNLP PubAnnotation server during BLAH3.17Bibliome2017-01-20Testing
AnEM_abstracts250 documents selected randomly from citation abstracts Entity types: organism subdivision, anatomical system, organ, multi-tissue structure, tissue, cell, developing anatomical structure, cellular component, organism substance, immaterial anatomical entity and pathological formation Together with AnEM_full-texts, it is probably the largest manually annotated corpus on anatomical entities.1.95 KNaCTeMYue Wang2016-06-07Released
AnEM_full-texts250 documents selected randomly from full-text papers Entity types: organism subdivision, anatomical system, organ, multi-tissue structure, tissue, cell, developing anatomical structure, cellular component, organism substance, immaterial anatomical entity and pathological formation Together with AnEM_abstracts, it is probably the largest manually annotated corpus on anatomical entities.689NaCTeMYue Wang2016-07-27Uploading
Annotation-Euglena-Enzymes0Shuichi Kawashima2016-06-13Developing
BioASQ-samplecollection of PubMed articles which appear in the BioASQ sample data set.0BioASQJin-Dong Kim2015-10-13Testing
BioLarkPubmedHPO228 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", 2015.7.24 KTudor Grozasimon2017-03-28Released
BioMedLATAnnotation of 643 questions from BioASQ with the Lexical Answer Type (LAT) and headword.02016-09-23Developing
BioNLP16_DUT6.5 KMessiy2017-06-01Testing
BioNLP16_Messiy6.5 KMessiy2017-06-02Testing
bionlp-st-bb3-2016-trainingEntity (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 KINRAYue Wang2017-05-22Released
bionlp-st-cg-2013-trainingThe training dataset from the cancer genetics task in the BioNLP Shared Task 2013. Composed of anatomical and molecular entities.10.9 KNaCTeMYue Wang2016-12-06Released
bionlp-st-epi-2011-trainingThe 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 KGENIAYue Wang2016-12-06Released
bionlp-st-ge-2016-corefCoreference 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 Kim2016-05-23Released
Name T# Ann.AuthorMaintainerUpdated_atStatus

1-20 / 160 show all
2015-BEL-Sample58Fabio RinaldiFabio Rinaldi2015-02-26Testing
2015-BEL-Sample-211.4 KFabio RinaldiNico Colic2016-05-25Released
Ab3P-abbreviations2.34 KSunghwan Sohn, Donald C Comeau, Won Kim and W John Wilburcomeau2016-07-29Beta
AIMed4.04 KThe University of Texas at AustinYue Wang2017-04-14Testing
Allie8.7 MDatabase Center for Life ScienceYasunori Yamamoto2017-04-06Developing
Alvis4Pubannotation0Ba2017-01-17Testing
AlvisNLP-Async-Test0Robert Bossyrbossy2017-04-07Testing
AlvisNLP-Test17Bibliome2017-01-20Testing
AnEM_abstracts1.95 KNaCTeMYue Wang2016-06-07Released
AnEM_full-texts689NaCTeMYue Wang2016-07-27Uploading
Annotation-Euglena-Enzymes0Shuichi Kawashima2016-06-13Developing
BioASQ-sample0BioASQJin-Dong Kim2015-10-13Testing
BioLarkPubmedHPO7.24 KTudor Grozasimon2017-03-28Released
BioMedLAT02016-09-23Developing
BioNLP16_DUT6.5 KMessiy2017-06-01Testing
BioNLP16_Messiy6.5 KMessiy2017-06-02Testing
bionlp-st-bb3-2016-training1.29 KINRAYue Wang2017-05-22Released
bionlp-st-cg-2013-training10.9 KNaCTeMYue Wang2016-12-06Released
bionlp-st-epi-2011-training7.6 KGENIAYue Wang2016-12-06Released
bionlp-st-ge-2016-coref853DBCLSJin-Dong Kim2016-05-23Released