The Brent lab is interested in how gene expression is regulated, how it affects phenotypes, and how it is affected by genetic variants. Our work includes fungi (baker's yeast and Cryptococcus neoformans, a fungal pathogen) and humans. Longstanding projects include determining which genes in yeast and Cryptococcus are regulated by each transcription factor (TF), using both computational and experimental methods. We are currently applying our computational methods for mapping TF targets to integrate a wide variety of human datasets. We are also developing models to predict the expression level of any gene in any individual from their genome sequence. In human genetics, we are members of the Long Life Family Study consortium, which aims to find genetic variants that confer long life and long health. This work involves integrating DNA sequence, DNA methylation, and gene expression data, in the context of networks and other knowledge bases that formalize biological knowledge. Our methods include traditional statistics, network analysis, and machine learning.

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