Mark L. Siegal is an Associate Professor in the Department of Biology and Center for Genomics and Systems Biology.
Dr. Siegal studies how complex biological traits evolve, by studying the gene networks that underlie the development of these traits. His work integrates experimental and computational approaches, and ranges from investigations of sexual development in fruit flies to analyses of microscopic differences in the shapes of yeast cells.
His work is supported by a National Science Foundation CAREER Award (2007–2012), and by research grants from the National Institutes of Health (2010–2014) and United States-Israel Binational Science Foundation (2010–2013).
Dr. Siegal’s work has appeared in top journals, including Nature, Development and Proceedings of the National Academy of Sciences. His 2003 Nature paper on complex gene networks was lauded in 2009 as an “Evolutionary Gem”, one of “15 examples published by Nature over the past decade or so to illustrate the breadth, depth and power of evolutionary thinking.”
In 2009, Dr. Siegal was honored with both the Golden Dozen Award for undergraduate teaching and the Graduate School of Arts & Science Outstanding Faculty Award. He has also been named a National Academies Education Fellow in the Life Sciences. Dr. Siegal teaches Applied Genomics, a course for graduate students and advanced undergraduates. The course provides an intensive, hands-on introduction to computational analysis of large-scale biological data sets. He also teaches Genomes and Diversity, a course for undergraduate non-science majors offered as part of NYU’s Morse Academic Plan (MAP). The MAP course explores how the study of genes is revolutionizing our understanding of the natural world.
Bergman A and Siegal ML, 2003. Nature 424:549–552.
Most species, including our own, are genetically diverse. In this paper, computational simulations were used to investigate how genetic diversity contributes to differences in observable traits. These simulations showed that, when many genes interact to produce a trait, the genes are expected to have a property called capacitance, whereby genetic differences accumulate without having an effect on the trait but can be suddenly revealed by a perturbation to the interaction network. Capacitance might have major implications for evolution because of the way it modulates how genetic diversity translates into trait diversity. Capacitance had previously been associated with a single gene, but this work suggested that many genes would show this property.
In 2009, Nature recognized this paper as an “Evolutionary Gem”, one of “15 examples published by Nature over the past decade or so to illustrate the breadth, depth and power of evolutionary thinking.”
Levy SF and Siegal ML, 2008. PLoS Biology 6:e264.
This paper used automated image analysis of microscopic yeast cells to identify capacitors, genes that modulate the observed degree of shape differences between cells. Hundreds of such genes were identified, and it was found that they occupy central positions in cellular networks.