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Jin-Dong Kim
User info
Collections
NameDescription Updated at
11-12 / 12 show all
Glycosmos6This collection contains annotation projects which target all the PubMed abstracts (at the time of January 14, 2022) from the 6 glycobiology-related journals: Glycobiology Glycoconjugate journal The Journal of biological chemistry Journal of proteome research Journal of proteomics Carbohydrate research 2023-11-16
LitCovid-sampleVarious annotations to a sample set of LitCovid, to demonstrate potential of harmonized various annotations.2021-01-14
Projects
NameTDescription# Ann.Updated atStatus
111-120 / 161 show all
LitCovid-PD-FMA-UBERON1.3 M2023-11-28Developing
NGLY1-deficiencyA collection of PubMed abstracts that may be related to NGLY1 deficiency.60.5 K2023-11-29Developing
preeclampsia_genes17.8 K2023-11-29Developing
Preeclampsia-compare67.2 K2023-11-29Testing
GO-CCAnnotation for cellular components as defined in the "Cellular Component" subtree of Gene Ontology17.6 K2023-11-30Developing
pubmed-enju-pasAnnotating PubMed abstracts for predicate-argument structure (PAS). Enju 2.4.2 is used to automatically compute PAS.19.1 M2023-11-24Developing
bionlp-st-ge-2016-reference-eval4262023-11-29Testing
LitCovid-PD-GlycoEpitope9992023-11-29Developing
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 K2023-11-29Released
ICD10Annotation for disease names as defined in ICD101.6 K2023-11-29Developing
Automatic annotators
NameDescription
31-40 / 40 show all
PD-GlycoEpitope-BA batch annotator using PubDictionaries with the dictionary 'GlycoEpitope'
Glycan-Motif-Image
PD-MAT
PD-CLO
PD-NCBITaxon
PD-UBERON-AE-2023It annotates for anatomical entities, based on the UBERON-AE-2023 dictionary on PubDictionaries. Threshold is set to 0.85.
Glycan-Image
Glycan-GlyCosmos
TextSentencersentence segmentation
PD-GlycoEpitope
Editors
NameDescription
1-1 / 1
TextAEThe official stable version of TextAE.