Selected Publications

1. Samanthe M. Lyons, Elaheh Alizadeh, Joshua Mannheimer, Katherine Schuamberg, Jordan Castle, Bryce Schroder, Philip Turk, Douglas Thamm, Ashok Prasad, Changes in Cell Shape Are Correlated with Metastatic Potential in Murine and Human Osteosarcomas, Biology Open 2016 5: 289-299; doi: 10.1242/bio.013409

2. Katherine A. Schaumberg, Mauricio S. Antunes, Tessema K. Kassaw, Wenlong Xu, Christopher S. Zalewski, June I. Medford, Ashok Prasad, Quantitative characterization of genetic parts and circuits for plant synthetic biology, Nature Methods, v13, 94-100 2016, doi: 10.1038/nmeth.3659 Published online on November 16, 2015

3. June Medford and Ashok Prasad, Plant Synthetic Biology takes root, Science, 346 no. 6206 pp. 162-163, October 2014

4. Chintan J. Joshi and Ashok Prasad, Epistatic interactions among metabolic genes depend upon environmental conditions, Molecular Biosystems, 2014, 10 (10), 2578 – 2589, doi: 10.1039/C4MB00181H

5. S. M. Lyons, W. Xu, J. Medford, Ashok Prasad (2014) Loads Bias Genetic and Signaling Switches in Synthetic and Natural Systems. PLoS Comput Biol 10(3): e1003533 (2014). doi:10.1371/journal.pcbi.1003533

6. Dipjyoti Das, Dibyendu Das and Ashok Prasad, Effective birth processes in microbial ecologies, Journal of Theoretical Biology, 308, 96-104, 2012

7. Dustin Robert Berger, Ketul Popat, Ashok Prasad, PCL Nanopillars Vs Nanofibers: A Contrast in Progenitor Cell Morphology, Proliferation, and Fate Determination, Advanced Engineering Materials, 14(6), B351-B356, 2012

8. S. M. Lyons, Ashok Prasad, Cross-talk and information transfer in mammalian and bacterial signaling, PLoS ONE 7(4): e34488. (2012) doi:10.1371/journal.pone.0034488

9. Ashok Prasad, Computational Modeling of Signal Transduction Networks: A Pedagogical Exposition,  Chapter 10 in “Computational Modeling of Signaling Networks”, Methods of Molecular Biology Series, edited by X. Liu and M. Betterton, Springer. 2012

10. Ashok Prasad, Julie Zikherman, Jayajit Das, Jeroem Roose, Arthur Weiss, Arup Chakraborty: Origin of the sharp boundary that discriminates positive and negative selection in thymocytes, Proceedings of the National Academy of Sciences 106, 528-533 (2009).

11. A. W. C. Lau, Ashok Prasad and Z. Dogic: Condensation of isolated semi-flexible filaments driven by depletion interactions, European Physical Letters 87, 48006 (2009)

12. Ashok Prasad, Howard Stone and Jane’ Kondev: Drift in Supported Membranes, Physics of Fluids, 19, 113103 (2007).

13. Vivek B. Shenoy, Dhananjay T. Tambe, Ashok Prasad and Julie A. Theriot
A kinematic description of the trajectories of Listeria monocytogenes propelled by actin comet tails, Proceedings of the National Academy of Sciences 104, 8229 (2007).

14. Yuko Hori, Ashok Prasad and Jane’ Kondev: Stretching short biopolymers by fields and forces, Physical Review E 75, 041904 (2007).

15. Ashok Prasad, Yuko Hori and Jane’ Kondev: Elasticity of semiflexible polymers in two dimensions, Physical Review E 72, 041918 (2005).
My research group works in a number of different areas at the intersection of the physical sciences and mathematics with biology. The main philosophical motivation is the belief that nontrivial biologically important phenomena arise as emergent properties from constituent parts. Part of the reason why we work on many different projects is the realization of the need for integrative explanations. Of course part of the reason is also that I find so many things interesting and worthy of study!

Reading information from the shapes of cells  (theory and experiment)

Mammalian cells have shapes that appear to be correlated with their function and their phenotype. We are trying to understand how cell shape is determined and what its relation is with cell properties. In a couple of recent papers and in ongoing work we have shown that there are subtle changes in cell shape that are correlated with increasing cancer invasiveness. We run a wet lab in which we do the experiments and we use image processing, machine learning and statistical data analysis to make inferences about cell shape changes.

Physical properties and nonequilibrium dynamics of the cellular cytoskeleton (theory and experiment)

Live cell imaging yields movies that are rich with movement. Organelles move around displaying both random walks and directed motion. The cell as a whole extends protrusions and the cytoskeleton breathes. Can we learn something about the underlying cytoskeletal mechanics by looking at internal cellular movement? We take movies of mitochondria and the whole cell, analyze the motion and try to interpret what we see. This is a very new project, but something that we are very excited about.

Development of synthetic gene circuits, especially in plants

Synthetic biology is an interdisciplinary field centrally concerned with the construction of synthetic control circuits in organisms. Ultimately it will help us create new technologies that could, depending upon how our species uses them, have major beneficial impacts. One of the reasons I am interested in synthetic biology is that it allows us to test our knowledge of how genetic circuits operate using predictive quantitative modeling and experiments.
We are currently working on developing methods to quantitatively test synthetic plant parts as well as developing the first synthetic switches in plants. Collaborator: June Medford, CSU Biology department.

Theoretical analysis of signal transduction and gene transcription.

There are literally hundreds of questions that can be probed by mathematical modeling of the relevant networks. The broad themes I am most interested in relate to questions related with biological complexity in gene networks and signal transduction. I am also interested in how biology encodes switches and how decisions are made by cells, as well as parallels and differences between cellular computation and computation performed by the brain. I am also interested in more specific biological questions such as understanding the structure of switches in T cell activation, in the cell cycle and in cancer.

Network analysis and gene expression data analysis to understand and help combat cancer.

This is a very new project in which we are currently using gene expression data to predict cancer disease outcome using machine learning and multivariate data analysis techniques. Collaborator: Dan Gustafson and Dawn Duval.

Modeling cyanobacterial metabolism for metabolic engineering

We are interested in the broad question of whether metabolism follows an optimization protocol. In the short term we use genome scale metabolic models to help metabolic engineers design methods for using cyanobacteria as chemical factories to produce, for example, biofuels.
We have currently built the most up to date and accurate model of Synechocystis metabolism so far, and are developing methods for dynamic analysis of day-night metabolism in cyanobacteria. Collaborator: Christie Peebles

© 2010 Ashok Prasad - site by Silvia Minguzzi