license: mit
task_categories:
- text-classification
language:
- en
tags:
- biology
- ner
- nlp
pretty_name: Cell/Tissue Dictionary
size_categories:
- 1K<n<10K
CellTissue-dict
This dictionary is comprised of a merge of two source dictionaries (from Bioportal and ChEMBL), used to tag cell and tissue descriptions in text.
Dataset Details
Dataset Description
- Curated by: Christine Withers
- Funded by: Open Targets
- Shared by: Christine Withers
- Language(s) (NLP): English
- License: MIT
Dataset Sources
This dictionary was produced by a combination of quick data sourcing, followed by partial manual categorising of terms.
- Repository: https://github.com/ML4LitS/OTAR3088
Direct Use
This data may be used to tag phrases in natural language, categorising them into broad bins 'CELL' and 'TISSUE'.
Out-of-Scope Use
This dictionary is by no means an exhaustive list of cell and tissue terms, the dictionary too does not ground terms to unique identifiers.
Dataset Structure
The 'term : label' entires here describe 'cell/tissue phrase' : 'CELL | TISSUE label'
E.g. 'HeLa' : 'CELL'
Dataset Creation
Curation Rationale
This data was used as a screen to quickly annotate texts, with the intention of these pre-annotated texts then being manually curated. Curated data were then used in a production pipeline for the creation of the CeLLaTe NER model.
Source Data
Source data was comprised of the ChEMBL cell dictionary, and a flattened dictionary of the BRENDA Tissue and Enzyme source ontology. Queries relating to ChEMBL dictionary extraction are located here: https://github.com/ML4LitS/OTAR3088/blob/main/Data_mining/chembl_sql/cell_line/cell_line_chembl_extraction.py BRENDA dictionary was sourced here: https://bioportal.bioontology.org/ontologies/BTO
Data Collection and Processing
The BRENDA dictionary, on downloading, was manually organised, labelling terms as either 'CELL' or 'TISSUE'. Dictionaries were concatenated in https://github.com/ML4LitS/OTAR3088/blob/main/Data_mining/labelstudio_e2e/labelstudio_e2e.py
Who are the source data producers?
Bioportal sourced the BRENDA dictionary, and ChEMBL the cell dictionary.
Citations:
- ChEMBL: Zdrazil B, Felix E, Hunter F, Manners EJ, Blackshaw J, Corbett S, de Veij M, Ioannidis H, Lopez DM, Mosquera JF, Magarinos MP, Bosc N, Arcila R, Kizilören T, Gaulton A, Bento AP, Adasme MF, Monecke P, Landrum GA, Leach AR. The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res. 2024 Jan 5;52(D1):D1180-D1192.
- Bioportal (BRENDA): Jennifer Vendetti, Nomi L Harris, Michael V Dorf, Alex Skrenchuk, J Harry Caufield, Rafael S Goncalves, John B Graybeal, Harshad Hegde, Timothy Redmond, Christopher J Mungall, Mark A Musen. BioPortal: an open community resource for sharing, searching, and utilizing biomedical ontologies. Nucleic Acids Research, Volume 53, Issue W1, 7 July 2025, Pages W84-W94, https://academic.oup.com/nar/article/53/W1/W84/8129374.
Dataset Card Authors
Christine Withers - https://huggingface.co/christine-withers
Dataset Card Contact
Christine Withers - https://huggingface.co/christine-withers withers@ebi.ac.uk