Dr. Dipak Barua

   Missouri University of Science and Technology
   210-L Bertelsmeyer Hall
   Rolla, MO 65409
   Phone: 573-341-7560
   E-mail: baruad@mst.edu
   Research website

   BS ChE, Bangladesh University of Engineering and Technology, 2002
   PhD ChE, North Carolina State University, 2008

Research Areas

Computational and Systems Biology, Modeling and simulation of cell signal transduction systems, Immunity and cancer, Distributed and parallel computing in systems biology applications

Research Statement

My research is focused on applying computational and sytems biology approaches to address problems in biology and medicine. I work on cell signal transduction systems relevant for immunity and cancer. One of my key research interests is to understand B lymphocyte (B cell) function. I study the mechanisms by which antigen-recognition activates B cells, and determine cell fate decisions. My research related to cancer cell systems is focused on Epidermal Growth Factor Receptor (EGFR) signaling and autophagy. My other area of interest is to develop parallel and distributed computing approaches for multiscale modeling.

Representative Publications

N. Kozer*, D. Barua*, S. Orchard, E. C. Nice, A. W. Burgess, W. S. Hlavacek, and A. H. A. Clayton, “Exploring higher-order EGFR oligomerisation and phosphorylation – a combined experimental and theoretical approach”, Molecular Biosystems 9, 1849-1863 (2013).

D. Barua and W. S. Hlavacek, “Modeling the effect of APC truncation on destruction complex function in colorectal cancer cells”, PLoS Computational Biology 9, e1003217 (2013).

D. Barua, W. S. Hlavacek, and T. Lipniacki, “A Computational Model for Early Events in B Cell Antigen Receptor Signaling: Analysis of the Roles of Lyn and Fyn”, The Journal of Immunology 189, 646-658 (2012).

K. R. Martin*, D. Barua*, W. S. Hlavacek, and J. P. MacKeigan, “Computational model for autophagic vesicle dynamics in single cells”, Autophagy 9, 74-92 (2013).

D. Barua*, J. Kim*, and J. L. Reed, “An automated phenotype-driven approach for refining metabolic and regulatory network models”, PLoS Computational Biology 6, e1000970 (2010).