faculty & research


Email: st2744@columbia.edu
Phone: 212-851-5166
Location Russ Berrie - 405A

The focus of our research is to understand the organizing principles that underlie the evolution and function of molecular networks. At one scale, we use large-scale genome-wide observations to reveal the “nuts and bolts” of these networks and to understand how they come together to orchestrate biological behavior.  At the other extreme, we aim to achieve a holistic understanding of function by considering the native ecological context in which these networks have evolved.  At the highest level, we aim to understand how molecular networks embody an internal representation of the outside world and facilitate adaptive behaviors. We have focused on these problems in the context of transcriptional regulatory and genetic networks of organisms ranging from bacteria to human.  In addition to using traditional experimental methods, we develop and employ novel technologies for making genome-wide observations, together with computational and analytic tools required to turn these observations into predictive models of the underlying biology.

Selected Publications

Goodarzi, H., Bennett, BD., Amini, S., Reaves, ML., Hottes, AK., Rabinowitz, J., Tavazoie, S. Regulatory and metabolic rewiring during laboratory evolution of ethanol tolerance in E. coli  Molecular Systems Biology 2010, 6:378

Goodarzi, H., Elemento, O., Tavazoie, S.  Revealing global regulatory perturbations across human cancers Molecular Cell 2009, 36:900-911


Vora, T., Hottes, AK., Tavazoie, S. Protein occupancy landscape of a bacterial genome. Molecular Cell 2009, 35(2):247-53


Tagkopoulos, I., Liu, Y., Tavazoie, S. Predictive behavior within microbial genetic networks. Science 2008, 320:1313-7


Elemento, O., Slonim, N., Tavazoie, S.  A universal framework for regulatory element discovery across all genomes and data-types. Molecular Cell  2007, 28, 337-350


Girgis, H., Liu, Y., Ryu, W., Tavazoie, S.  A comprehensive genetic characterization of bacterial motility.  PLoS Genetics 2007, 3(9): e154


Beer MA, Tavazoie S. Predicting gene expression from sequence. Cell 2004 117:185-98.