| epi-statement-test | | | 2 | 2023-11-30 | Testing | |
| test_lasige | | | 494 | 2023-12-02 | Testing | |
| GO-MF | | Annotation for molecular functions as defined in the "Molecular Function" subtree of Gene Ontology | 19.7 K | 2023-12-04 | Testing | |
| LitCovid-PD-MONDO | | | 2.26 M | 2023-11-24 | | |
| twitter-test | | | 13 | 2023-11-28 | Developing | |
| 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 K | 2023-11-29 | Released | |
| GlyCosmos600-FMA | | | 13.8 K | 2024-09-12 | | |
| GlyCosmos-GlycanStructure-c | | | 0 | 2023-11-29 | Testing | |
| glycobiology-test | | | 27 | 2023-11-29 | Developing | |
| 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 K | 2023-11-27 | Released | |
