Amanda Everitt

UC San Francisco

“Using Genomic Footprinting to Reveal Cell Type-Specific Transcription Factor Grammar”

One DNA template can result in seemingly endless cellular states because of proteins called transcription factors, and how they bind to DNA. My goal is to develop new statistical and machine learning frameworks that will allow us to understand their binding process at finer resolutions than currently possible.


Transcription factors (TFs) are regulatory proteins that directly bind to DNA in order to impact gene expression. They play a major role in shaping how the same DNA template can result in seemingly endless cellular states. This project focuses on building new computational methods for determining active TF binding sites with an emphasis on how precise patterns of TFs relate to cell type distinctions in neurodevelopmental and disease contexts. I aim to provide a new path in single-cell analysis through which we can understand TF regulation at a finer resolution than currently possible.

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