Computational Systems Biology involves studying cellular functions and its components at varying degrees of granularity. These levels range from the nano-scale molecular structures (atomic level) to entire organs such as heart and lungs (phenotype level). Our research focus is mainly on the dynamics of Biopathways.

Complexity Spectrum of Biological Systems

 

Biopathways

The mechanisms driving the cell are realized by vast networks of chemical reactions. Aside from transcription and translation, the various organic molecules undergo other processes such as phosphorylation, dephosphorylation, translocation, association, dissociation etc. The resulting 'circuitry' of reactions are often drawn as graphs and referred as pathway diagrams.

 

Broadly speaking, there are three main classes of biopathways:

  • Metabolic Pathways
  • Signaling Pathways
  • Gene Regulatory Networks

Here at the Computational Systems Biology group at NUS, we are particularly interested in modeling and analyzing Signaling Pathways. We aim to however develop techniques which will have a wider range of applicability.

Currently we interact with biologists in the Department of Biochemistry, Department Physiology and the Department of Biological sciences in NUS. We are also in the process of developing collaborations with the RCE in Mechanobiology.
 

Modeling Framework

Modeling methods in this domain are either qualitative (e.g. Boolean networks) or quantitative (e.g. Ordinary Differential Equations). We are using a variety of formalisms, both qualitative and quantitative: Ordinary Differential equations, Hybrid Functional Petri Nets, Markov Chains, Dynamic Bayesian Networks etc.

 

Research Areas

Below is a list of bio-pathways and computational problems that we are currently exploring.

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