Strategies for effectively modelling promoter-driven gene expression using transfer learning.

ABSTRACT: The ability to deliver genetic cargo to human cells is enabling rapid progress in molecular medicine, but designing this cargo for precise expression in specific cell types is a major challenge. Expression is driven by regulatory DNA sequences within short synthetic promoters, but relatively few of these promoters are cell-type-specific. The ability to design cell-type-specific promoters using model-based optimization would be impactful for research and therapeutic applications. However, models of expression from short synthetic promoters (promoter-driven expression) are lacking for most cell types due to insufficient training data in those cell types. Although there are many large datasets of both endogenous expression and promoter-driven expression in other cell types, which provide info

SUBMITTER: Reddy AJ 

PROVIDER: S-EPMC10002662 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature