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==Suresh Kumar Poovathingal==
==Suresh Kumar Poovathingal==
[[Image:Suresh lab crop.jpg|300px|right|Suresh Kumar Poovathingal]]
[[Image:Suresh lab crop.jpg|300px|right|Suresh Kumar Poovathingal]]
Department of Chemical and Biomolecular Engineering
Department of Chemical and Biomolecular Engineering<br>
National University of Singapore
National University of Singapore<br>
4 Engineering Dr. 4 Blk E5 #02-16
4 Engineering Dr. 4 Blk E5 #02-16<br>
Singapore 117576
Singapore 117576<br>
Tel:+65 6516 7859
Tel:+65 6516 7859
[[Special:Emailuser/Suresh Poovathingal|Email me through OpenWetWare]]
[[Special:Emailuser/Suresh Poovathingal|Email me through OpenWetWare]]

Revision as of 03:39, 31 July 2008

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Chemical and Biological Systems Engineering Laboratory

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Suresh Kumar Poovathingal

Suresh Kumar Poovathingal
Suresh Kumar Poovathingal

Department of Chemical and Biomolecular Engineering
National University of Singapore
4 Engineering Dr. 4 Blk E5 #02-16
Singapore 117576
Tel:+65 6516 7859 Email me through OpenWetWare

I work in the Dynamical BioSystems Lab at National University of Singapore.


Education

  • 2006, MS, Technische Universitaet Hamburg-Harburg, Germany
  • 1999, BEngg, B.M.S College of Engg, Bangalore University, India

Research interests

  • Reverse Engineering of Biological systems

The mitochondrial free radical theory of aging (mFRTA) implicates reactive oxygen species (ROS) as the causative agent for the degeneration of mitochondrial genome integrity and cellular respiratory function resulting in the tissue dysfunction. Although several premises of mFRTA are still intensely debated, the role of mitochondria and ROS in aging has been supported by the transgenic mice studies. At the moment, there is no definitive explanation about the mechanisms by which somatic mtDNA mutations expand in an organism’s life. Our motivation to implement a stochastic modeling approach stems from the inadequacies of the current practice in elucidating the dynamics and mechanism of mtDNA instability from data, which were obtained through standard but suboptimal experimental protocols. Further complicating this problem is the fact that the cellular processes are inherently noisy. In order to capture these uncertainties, we have developed a minimal stochastic mutation model based on the Chemical Master Equation (CME). The model was used for simulating point mutation burden in several cell lines of both the wild-type and transgenic mice. All the parameters used for modeling were derived from the literature. The simulation outcomes were validated against published experimental data. Our preliminary investigation elucidated two sources of uncertainties and the coupling of these uncertainties can introduce large enough noise that prevents a conclusive deduction of mtDNA mutation dynamics, even using the state-of-the-art experimental technique. Further, the developmental stages and cell divisions in an organism were found to have a significant contribution in initiating the mitochondrial genome instability. Such significant effect of noise motivates an integration of in silico, in vivo and in vitro experiments in future aging studies.

  • Stochastic Analysis
  • Aging and Degenerative diseases


Publications

  1. [Paper1]

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