Assistant Professor of Biochemistry & Molecular Biology
Computational biology for understanding gene regulation
New experimental approaches based on DNA sequencing are allowing us to see where various gene regulatory processes are happening along the genome. However, these experiments produce vast amounts of data, and so turning them into an understanding of the regulatory circuitry controlling cells remains a huge challenge. The Mahony lab aims to meet this challenge by developing machine learning algorithms for detecting patterns in large regulatory genomics datasets. In particular, we focus on understanding how transcription factors and other regulatory proteins control cell behavior during development and cellular programming. We need motivated undergraduate students to help us to analyze regulatory genomics datasets and to help develop bioinformatics tools for data mining and visualizing large collections of genomics data.