Srivastava, Ranjan

Ranjan Srivastava, Ph.D.
Professor & Head
Chemical, materials, and biomolecular engineering
Research Interests:
Infectious pathogens, cancer systems biology, cellular engineering, computational biology tool development. 
191 Auditorium Road, Unit 3222
Storrs, CT 06269 
Office Phone(860) 486-2802
Fax(860) 486-2959
B.S. ChE, Washington University in St. Louis
M.S. ChE, University of Maryland, College Park
Ph.D. ChE, University of Maryland, College Park
NIH Post-Doctoral Trainee, ChE & Oncology, University of Wisconsin, Madison 

Research Summary:

Our research focuses on understanding and manipulating complex biological interactions at the cellular and sub-cellular levels using a combination of computational and experimental approaches. We focus primarily on problems in the areas of infectious dieases, cancer systems biology, and cellular engineering.

To carry out our work, we leverage knowledge from a wide variety of disciplines, including chemical engineering, molecular biology, applied mathematics, machine learning, and systems optimization. In addition to pushing the boundaries of our current understanding, it is our hope that the work will lead to direct benefits for society.

Information about current research projects can be found at

Selected Publications:
  1. Bautista EJ and Srivastava R (2014) Enhancing genetic algorithm-based genome-scale metabolic network curation efficiency. Proceedings of the 2014 conference on Genetic and evolutionary computation. 257-264, doi: 10.1145/2576768.2598218 
  2. Bautista EJ, Zinski J, Szczepanek SM, Johnson EL, Tulman ER, Ching WM, Geary SJ, Srivastava R (2013) Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum. PLoS Comp Bio. 9(9):e1003208. doi: 10.1371/journal.pcbi.1003208. 
  3. Peterson DE, Srivastava R, and Lalla RV (2013) Oral Mucosal Injury in Oncology Patients: Perspectives on Maturation of a Field. Oral Diseases. doi: 10.1111/odi.12167. 
  4. Bautista EJ and Srivastava R (2013) Leveraging ensemble information of evolving populations in genetic algorithms to identify incomplete metabolic pathways. Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, 39-40, doi: 10.1145/2464576.2464601. 
  5. Johnson E and Srivastava R (2012) Volatility in mRNA Secondary Structure as a Design Principle for Antisense. Nucleic Acids Research, doi: 10/1093/nar/gks902.