Final Report Summary - COSBICS (Computational systems biology of cell signalling)
The ultimate aim of the COSBICS project was to establish and apply a novel computational framework to investigate dynamic interactions of molecules within cells. More specifically, it aimed to identify and quantify dynamic interactions of signalling pathways using system and signal-oriented approaches, as well as develop methodologies applicable to the dynamic and predictive analysis of signalling networks. The project studied two certain pathways and combined mathematical modelling with biological knowledge in an effort to improve the understanding on how two particular central communication networks were subverted in tumour cells.
The tools developed for the mathematical analysis of non-linear signal transduction pathway models were generic and could be applied in other systems biology projects, as well. The project aimed to develop models that could predict the biochemical behaviour of pathways in response to perturbations, which would be experimentally tested. This information would also be used to aid in the design of biological experiments, e.g. by determining how many measurements need to be taken at what time intervals for a robust result to be obtained. Both applications would be useful for academic, as well as industrial research mainly through minimising the 'wet' experimental load which is very expensive and time consuming.
The tools developed for the mathematical analysis of non-linear signal transduction pathway models were generic and could be applied in other systems biology projects, as well. The project aimed to develop models that could predict the biochemical behaviour of pathways in response to perturbations, which would be experimentally tested. This information would also be used to aid in the design of biological experiments, e.g. by determining how many measurements need to be taken at what time intervals for a robust result to be obtained. Both applications would be useful for academic, as well as industrial research mainly through minimising the 'wet' experimental load which is very expensive and time consuming.
