Gunawan:Thanneer Malai

Chemical and Biological Systems Engineering Laboratory

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Thanneer Malai Perumal

Thanneer Malai Perumal

National University of Singapore
4 Engineering Drive 4 Block E5 #B-05
National University of Singapore
Singapore 117576

I work for Rudiyanto Gunawan at National University of Singapore (NUS).

Education

• 2006, BE, National Institute of Technology Karanataka, Surathkal.

Awards/Accolades

• 2008-2012, Recipient of Singapore Millennium Foundation(SMF) scholarship.

Research interests

Robustness Analysis in Systems Biology

Through millennia of evolution, cells have developed intricate networks of signalling, gene regulation, and metabolism to accomplish their myriad functions under significant intrinsic and extrinsic uncertainties. As the knowledge of cellular components and their interactions grows, the understanding of how a cellular behaviour or function is accomplished in large and complex networks becomes non-intuitive, giving motivation to the use of mathematical modeling and systems analysis. On the other hand, advanced technology is creating examples of networks where we do know all the details and that have complexity approaching that of biology. While the components are entirely different, there is striking convergence at the network level of the architecture and the role of protocols, layering, control, and feedback in structuring complex system modularity. Since this apparent network-level evolutionary convergence both within biology and between biology and technology is not accidental, and follows necessarily from the requirements that both biology and technology be efficient, robust, adaptive, and evolvable. And thus analyzing robustness, a systems level property, will help us to understand the cellular networks better.

The focus of our research is in developing novel robustness measures and analysis methodologies for both deterministic and stochastic models of cellular signalling networks. Of particular interest is the development of an effective sensitivity based methodology named Two-Time Molecular Sensitivity (TTMS) analysis complementing the existing Parametric Sensitivity analysis. We have also successfully developed a novel local TTMS analysis for deterministic models and applied to various cellular signalling pathways. In general, TTMS analysis offers dynamical insights on the functional regulation and signal propagation in the cellular network of interest. The results give a molecule-by-molecule account of how a network function or output is accomplished. In practice, the analysis can guide model identification and reduction of cellular systems and suggest experimentally testable hypotheses. In addition, the biological knowledge gained can assist drug discovery efforts in the identification of potential drug targets, the understanding of drug efficacy and specificity, and finally the optimization of drug dosing and timing. The development of this method represents a concrete step towards robustness-based drug design through systems biology.

Key words: Systems Biology, Mathematical model, Sensitivity analysis, Robustness, Systems Oriented Drug Discovery

Useful links

• Our Lab webpage