Probing the evolution of transcription factor activation domains
Max Staller, Assistant Researcher
Center for Computational Biology
Closed. This professor is continuing with Fall 2024 apprentices on this project; no new apprentices needed for Spring 2025.
Transcription factors contain DNA binding domains and separate activation domains that bind coactivator complexes. DNA binding domains are conserved, structured and can be predicted from amino acid sequence. Activation domains are intrinsically disordered (they do not fold into a single 3D structure), poorly conserved and cannot be predicted from amino acid sequence. This project will investigate activation domains from different species of yeast to understand how activation domains evolve. We have evidence that sometimes function is conserved but sequence is not conserved and we believe that these instances will help build better machine learning models for predicting activation domains from protein sequence.
Role: Comparative genomics of transcription factors. The student will learn to search genome databases for othologous proteins with BLAST and HMMER. They will build new Multiple Sequence Alignments of transcription factors and look for which residues are more or less conserved in known activation domains.
Qualifications: Coursework in introductory biology. Some exposure to evolutionary biology.
Computer programming in python is required.
In your essay, please describe any experience with 1) Savio 2) querying online databases 3) command line programming and 4) analysis in R. Experience with all 4 is not necessary, but each will be helpful.
Hours: 9-11 hrs
Biological & Health Sciences