NIH R01 · 2025
Decoding disease-critical genomic architecture using multimodal single-cell omics data
Project Summary/Abstract Understanding the functional architecture of human diseases and traits at a cellular resolution is critical for informing follow-up functional characterization experiments and nominating genes and pathways for developing drug targets. Large scale omics data encompassing multiple modalities (RNA-seq, ATAC-seq, ChiP-seq), a broad range of tissues and cell types, and diverse biological contexts, such as disease stages, developmental trajectories, and gene perturbations, offer significant new resources to gain a deeper understanding of the genetic architecture of complex diseases. In this proposal, we plan to develop statistical and machine learning approaches that…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.