The Dowell lab seeks to uncover the core principles behind the genetics of transcription. Specifically, we use a number of experimental and computational approaches to compare closely related individuals to discover the underlying mechanistic principles of transcriptional regulation. In yeast, we use naturally occurring strains, molecular biology, and genetics to identify the mechanistic basis of differential transcriptional regulation. In humans, we have been using global run-on sequencing (GRO-seq) to study nascent transcription. As much of our work leverages novel data, such as global run-on sequencing (GRO-seq), or integrates across diverse large-scale datasets (RNA-seq, ChIP-seq, GRO-seq, 3-seq, etc), we must frequently develop new computational approaches in order to answer interesting biological questions.
Computational biology, comparative genomics, systems biology, machine learning, probabilistic modeling, Down syndrome, personalized medicine