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NameTDescription# Ann.AuthorMaintainerUpdated_atStatus

61-80 / 553 show all
spacy-test Random 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.131 KNico ColicNico Colic2021-03-10Released
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 MIBI GroupYue Wang2021-03-11Released
2015-BEL-Sample-2 The 295 BEL statements for sample set used for the 2015 BioCreative challenge.11.4 KFabio RinaldiNico Colic2021-03-11Released
bionlp-st-ge-2016-reference It is the benchmark reference data set of the BioNLP-ST 2016 GE task. It includes Genia-style event annotations to 20 full paper articles which are about NFκB proteins. The task is to develop an automatic annotation system which can produce annotation similar to the annotation in this data set as much as possible. For evaluation of the performance of a participating system, the system needs to produce annotations to the documents in the benchmark test data set (bionlp-st-ge-2016-test). GE 2016 benchmark data set is provided as multi-layer annotations which include: bionlp-st-ge-2016-reference: benchmark reference data set (this project) bionlp-st-ge-2016-test: benchmark test data set (annotations are blined) 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.14.4 KDBCLSJin-Dong Kim2021-07-28Released
LitCovid-docs-s 0Jin-Dong Kim2021-10-18Released
LitCovid-OGER-BB Using OGER (www.ontogene.com) and Biobert to obtain annotations for 10 different vocabularies.308 KFabio RinaldiNico Colic2021-10-18Released
Zoonoses_partialAnnotation This is a part of Zoonoses project used by PanZoora. But Zoonoses project provides whole manual annotated data but this is partial ones.266AikoHIRAKI2021-12-01Released
TEST-DiseaseOrPhenotypicFeature Annotated by Mesh_All_FN795Eisuke Dohi2021-12-23Released
geneset_names 0alo332022-04-26Released
Inflammaging Inflammation axis23.4 Malo332022-06-08Released
CORD-19-PD-MONDO PubDictionaries annotation for MONDO terms - updated at 2020-04-30 It is disease term annotation based on MONDO. Version 2020-04-20. The terms in MONDO are loaded in PubDictionaries, with which the annotations in this project are produced. The parameter configuration used for this project is here. Note that it is an automatically generated dictionary-based annotation. It will be updated periodically, as the documents are increased, and the dictionary is improved.6.32 MJin-Dong Kim2022-06-14Released
LitCovid-OGER Using OGER (http://www.ontogene.org/resources/oger) to detect entities from 10 different vocabularies9.31 KFabio RinaldiNico Colic2022-09-01Released
Genomics_Informatics Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Text corpus for this journal annotated with various levels of linguistic information would be a valuable resource as the process of information extraction requires syntactic, semantic, and higher levels of natural language processing. In this study, we publish our new corpus called GNI Corpus version 1.0, extracted and annotated from full texts of Genomics & Informatics, with NLTK (Natural Language ToolKit)-based text mining script. The preliminary version of the corpus could be used as a training and testing set of a system that serves a variety of functions for future biomedical text mining.35.3 KHyun-Seok Parkewha-bio2018-11-27Beta
LitCovid-PAS-Enju Predicate-argument structure annotation produced by the Enju parser.125 KJin-Dong Kim2020-03-25Beta
blah6_medical_device BLAH6 hackathon project to annotate medical device indications in premarket approval statement summaries. The documents in this project serve as a corpus of premarket approval (PMA) statements that have undergone quality control. In particular, we have (1) removed non-ascii characters, (2) fixed some text segmentation errors, and (3) fixed some capitalization errors.0Stefano Rensitherightstef2020-08-04Beta
FA_Top107-forWeb ※※※ !要データ加工! webリンク用には、この結果を加工して使っています。その他で使われる場合に、末尾記載の問題を別途解決する必要があります。 !要データ加工! ※※※ Top100+本来Top100に入るべきだった7レビューの計、107レビュー中99レビュー。 5414, 6076, 6930, 8403, 9643, 12112, 18544, 18829は、0denotationでドキュメント自体登録していません。 @AikoHIRAKIはtypoを修正したレビューフォルダ。 attributesの詳細はconfig参照。 ※※※ !注意! webリンク側のしばりで、選択文字列は複数のUniProtIDに対応していません。(例)Protein1~Protein7とある場合、 Protein1, 2, 3, 4, 5, 6, 7をさし、かつ全てにUniProtIDがあったとしても、1と7のみUniProtIDをとってきています。 "~"は、Protein2, 3, 4, 5, 6を意味していますが、positionではなく文字列で検索をかけているのと、見せ方の仕様上、これらのIDは全て未取得となっています。⇔GeneProteinでは"~"に2-6のIDsをもたせていました。 該当レビュー;14898(~=MAPK2, MAPK3, MAPK4, MAPK5, MAPK6), 10471(~=Ago2, Ago3) --------------------------------------- (例)ProteinAB...ProteinCD...ProteinB...ProteinDとある場合、 ProteinABは、ProteinAとBというLexical_Cueになっています。ProteinCDも同様に、ProteinCとD。BとDだけでは、このレビュー内ではProteinBやProteinDをさすことが分かるのですが、それ以外で使用する場合に、BとDにそれぞれ該当UniProtIDをあてるのは不適切です。 該当レビュー;11957(β4=itgb4, β1=itgb1, β5=itgb5, β3=itgb3) 他の例が出てきたら順次、ここに記載していきます。当座、これらは削除する必要があります。 attributeで削除フラグをつけるか、Jakeの機能がTextAEに実装されれば解決するか、検討して、何かしら分かるようにしておきます。 (例)ProteinA/B とある場合、 webリンクでは、"ProteinA"にUniProtID-Aを、"/B"にUniProtID-Bをつけています(リンク側のしばり)。webリンク以外で使われる場合には、別プロジェクトのFA_Top100Plus-GeneProteinで行っていたようなRelationを使って、"/B"ではなく、"ProteinB"として、UniProtID-Bと対応させる必要があります。現状のとり方ですと、要Relation箇所は救済出来ません。 Lexical cueには"/B"とありますが、Objectには"ProteinB"と残してあるので、Objectを参照して下さい。 但し、言語処理のようなpositionがご入用な場合には上では対応出来ていません。 該当レビュー;11935(/4=BMP4), 14898(/2=LATS2), 7412(/2=TSC2), 4629(/2=CtBP2) (webリンクでは、レビュー毎に完結しているので、"/B"がそのレビューで他の意味をなしていなければ対応出来るのと、文字列合致でリンクを貼っているためです。) !注意! ※※※ RelationのmergedはTextAEの既存機能で既に出来ます。10.3 KAikoHIRAKI2020-09-01Beta
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 Kim2020-10-02Beta
Age_blah 1.9 Kslee72682020-11-03Beta
LitCovid-sample-sentences 2.3 KJin-Dong Kim2021-01-14Beta
LitCovid-sample-PD-FMA 1.93 KJin-Dong Kim2021-01-14Beta
NameT# Ann.AuthorMaintainerUpdated_atStatus

61-80 / 553 show all
spacy-test 131 KNico ColicNico Colic2021-03-10Released
DisGeNET5_gene_disease 2.04 MIBI GroupYue Wang2021-03-11Released
2015-BEL-Sample-2 11.4 KFabio RinaldiNico Colic2021-03-11Released
bionlp-st-ge-2016-reference 14.4 KDBCLSJin-Dong Kim2021-07-28Released
LitCovid-docs-s 0Jin-Dong Kim2021-10-18Released
LitCovid-OGER-BB 308 KFabio RinaldiNico Colic2021-10-18Released
Zoonoses_partialAnnotation 266AikoHIRAKI2021-12-01Released
TEST-DiseaseOrPhenotypicFeature 795Eisuke Dohi2021-12-23Released
geneset_names 0alo332022-04-26Released
Inflammaging 23.4 Malo332022-06-08Released
CORD-19-PD-MONDO 6.32 MJin-Dong Kim2022-06-14Released
LitCovid-OGER 9.31 KFabio RinaldiNico Colic2022-09-01Released
Genomics_Informatics 35.3 KHyun-Seok Parkewha-bio2018-11-27Beta
LitCovid-PAS-Enju 125 KJin-Dong Kim2020-03-25Beta
blah6_medical_device 0Stefano Rensitherightstef2020-08-04Beta
FA_Top107-forWeb 10.3 KAikoHIRAKI2020-09-01Beta
bionlp-st-ge-2016-uniprot 16.2 KDBCLSJin-Dong Kim2020-10-02Beta
Age_blah 1.9 Kslee72682020-11-03Beta
LitCovid-sample-sentences 2.3 KJin-Dong Kim2021-01-14Beta
LitCovid-sample-PD-FMA 1.93 KJin-Dong Kim2021-01-14Beta