Integrating single-cell based transcriptomic signatures for identifying therapeutic targets of COPD
Description: Project Narrative This proposal aims to apply machine learning and network methods in the study of COPD, with integration of single cell RNAseq data from a smaller cohort of severe patients and bulk-level RNAseq data from large cohorts. The proposed study will identify (i) a list of prioritized transcription factors and pathways that are most likely to mediate the gene expression change observed in different cell types and (ii) a list of drugs that are most likely to target these transcription factors and pathways. Ultimately, such knowledge is essential for developing novel drug targets and treatment strategies for COPD patients, thereby improving public health.
Funding type: research
Funder scheme: R21
Start date: 2022-01-01
End date: 2023-12-31
Investigator: NAFTALI KAMINSKI
Institution: YALE UNIVERSITY
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Funded outputs count: 18
Funder award ID: R21HL161723
OpenAlex ID: G2031262966