Chen Lab

Research focus

NIH R01 · 2024

Geometric structures guided learning model and algorithms for bulk RNAseq data analysis

Discovering potential drugs and treatments of many diseases heavily depends on identifying differentially expressed (DE) genes in disease conditions within individual cell types. While it is possible to experimentally sort out cells of individual cell types for DE analysis, computationally leveraging bulk tissue data has the advantage of greater availability, lower expenses, and less human handling. A critical step toward this research is to (completely) deconvolute gene expressions in specific cell types from the heterogeneous bulk tissues. Complete deconvolution can be viewed as a nonnegative matrix factorization (NMF) problem, however, NMF is strongly ill-posed, and its non-separable…

From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.