Abstract
Biomarker reflects an underlying biological state or identity. Extensive kidney studies have resulted in the discovery of many kidney cell and disease biomarkers. Our manual literature annotations have identified 150 cell-specific markers for 73 kidney cell types and 38 diabetic kidney disease (DKD)-related biomarkers. To systematically study these biomarkers, we first surveyed and ontologically defined the term biomarker and different types of biomarkers. The Kidney Tissue Atlas Ontology (KTAO) has been further used as a platform to model and represent these kidney biomarkers by including the biomarker gene name, cell type, disease, and axioms linking the biomarkers and other terms. Gene Ontology (GO) analysis revealed 9 shared enriched GO terms in both biomarker sets. A DL-query was performed to demonstrate the advantages of ontology-based modeling and analysis of kidney biomarkers.
| Original language | English |
|---|---|
| Pages (from-to) | 70-76 |
| Number of pages | 7 |
| Journal | CEUR Workshop Proceedings |
| Volume | 3073 |
| State | Published - 2021 |
| Event | 2021 International Conference on Biomedical Ontologies, ICBO 2021 - Bozen-Bolzano, Italy Duration: Sep 16 2021 → Sep 18 2021 |
Keywords
- DKD
- KTAO
- Kidney biomarker
- Ontology