Stochastic Inference of Regulatory Networks Inside Living Cells

January 18, 2013, Webb 1100

Abhyudai Singh

University of Delaware, Electrical & Computer Engineering


In the noisy cellular environment many mRNA and protein species occur at low integer molecular counts, and hence are subject to large stochastic fluctuations in copy numbers over time. Far from being a hindrance, signatures of Protein/mRNA noise levels can be informative about the underlying gene network topology. In this talk, I will present recently developed mathematical techniques that harness fluctuations in the levels of biochemical species for systems identification of gene regulatory networks. Finally, I describe our current efforts is using these techniques for reverse engineering the genetic circuitry of the Human immunodeficiency virus (HIV).

Speaker's Bio

Abhyudai Singh earned his bachelor’s degree in mechanical engineering from the Indian Institute of Technology in Kanpur, India. He received master’s degrees in both mechanical and electrical & computer engineering from Michigan State University, and a master’s degree in ecology, evolution and marine biology from University of California Santa Barbara (UCSB). After earning his doctoral degree in electrical & computer engineering in 2008, also from UCSB, he completed postdoctoral work in UC San Diego’s Department of Chemistry and Biochemistry. Since 2011 he is an assistant professor in electrical & computer engineering at University of Delaware.   

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