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 languageEnglish
Pages (from-to)70-76
Number of pages7
JournalCEUR Workshop Proceedings
Volume3073
StatePublished - 2021
Event2021 International Conference on Biomedical Ontologies, ICBO 2021 - Bozen-Bolzano, Italy
Duration: Sep 16 2021Sep 18 2021

Keywords

  • DKD
  • KTAO
  • Kidney biomarker
  • Ontology

Fingerprint

Dive into the research topics of 'Ontology-based Modeling, Representation, and Analysis of Biomarkers in Healthy and Disease Kidney Tissue'. Together they form a unique fingerprint.

Cite this