Computational and Systems Biology

Computational and Systems Biology

 The goal of the Computational and Systems Biology Program is to train the next generation of scientists in technology intensive, quantitative, systems level approaches to molecular biology. We aim to graduate students who are as comfortable operating the latest high end instrumentation as they are manipulating the mathematical formalisms that are required to make sense of their data. It is our hope that the students who join the Computational and Systems Biology Program will apply these approaches to unraveling the complex genetic circuits that control the cell. 

Areas of Study: Systems biology; Genomics; Sequence analysis; Regulatory Systems; networks; Synthetic biology; Metagenomics; Metabolomics; Proteomics; Epigenomics; Transcriptomics; Lipidomics; Single cell dynamics; High-throughput technology development; Applied math and mathematical models of biological processes; Computational biology; Comparative genomics; Personalized medicine; Genome engineering; Machine learning; Big data science; Next generation sequencing and its applications; Bioinformatics