Computational reconstruction of a TGF beta-Smad network

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Systems biology is an interdisciplinary research challenge that is critical for maintaining and developing world-class research excellence in the UK. The integration of biology, mathematics and computer science in systems biology will promote the development of computational models of complex biological networks. One such network of clinical significance involves the cytokine TGFb, transcription factors of the Smad family and calmodulin kinase II (CaMKII). TGFb and members of the TGFb family have been implicated in wound healing and in disorders such as cancer and fibrosis. TGFb induces the nuclear localization of Smad, whereas CaMKII inhibits it. Our goal is to implement the construction of computational models of this network following three distinct approaches: (1) Agent-based modelling, in which there is a one-to-one correspondence between individual entities and software programs. (2) Hydrid functional Petri net modelling, a graphical approach widely used for modelling complex dynamic systems in engineering. (3) Deterministic modelling, using ordinary differential equations. We will compare model performance to experimental data and assess model functionality in relation to practical and theoretical elements of network biology.