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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
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Associating pathways with diseases using single-cell expression profiles and making inferences about potential drugs.
Madhu Sharma1, Indra Prakash Jha1, Smriti Chawla1
1Department of computational biology, Indraprastha Institute of Information Technology, Okhla Ph-III, New Delhi.
Briefings in Bioinformatics
|June 30, 2022
Summary
We developed a novel method for single-cell expression analysis to uncover genetic pathway-disease links. This approach aids in understanding disease mechanisms and developing precision therapies, validated using diabetes models.
Area of Science:
- Genomics
- Systems Biology
- Computational Biology
Background:
- Identifying direct links between genetic pathways and diseases is crucial for applications like precision therapy.
- Previous bulk expression studies faced limitations due to cellular heterogeneity and sample size.
Purpose of the Study:
- To introduce a novel method, single-cell expression-based inference of association between pathway, disease and cell-type (sci-PDC), for dissecting pathway-disease-cell-type relationships.
- To enable a deeper understanding of disease causality and guide the development of targeted therapies.
Main Methods:
- Developed the sci-PDC method utilizing single-cell expression data.
- Applied sci-PDC to infer associations between pathways, diseases, and cell types.
- Utilized the diabetes model to track pathway-disease association variations across age and species.
Main Results:
- Highlighted reliable associations between specific diseases and genetic pathways.
- Demonstrated the utility of sci-PDC in tracking dynamic pathway-disease associations.
- Revealed insights into the suitability of mouse models for studying human diseases like diabetes.
Conclusions:
- The sci-PDC method provides a reliable tool for multidimensional analysis of pathway-disease associations.
- Results align with previous findings and offer potential for identifying drug target pathways.
- The study underscores the importance of single-cell resolution for accurate disease mechanism elucidation.
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