Research proposal in Systems Biology - Essay Example

BETTER UNDERSTANDING BIOLOGICAL PATHWAYS THROUGH QUANTITATIVE CELL SIMULATIONS The scientific exploration of quantitative cell simulations should enable a broader understanding of biological pathways. The use of quantitative synthetic cell simulations of cellular genes and proteins has, in recent times, proven especially elucidative on the hitherto complicated mechanism of biological pathways. In fact, "many high throughput techniques have been discovered which enable a precise simultaneous monitoring of the expression of thousands of genes," (Goldbeter, 1996) and significant progress has been made toward precise and mathematical appreciation not only of individual entities but also of the interaction and inter-relationship of components of biological pathways.

For instance, "power techniques like RNAi for the first time enables a very precise perturbation of parts of biological pathways," (Goldbeter, 2002) and development in fluorescent techniques offers us for the first time the possibility to measure mobility of single molecule in a living system and the distances and interaction of protein in vivo or calcium concentration in Cytoplasm or organelles (Goldbeter). It is no longer news that reconstructing genetic circuits into synthetic replicas may afford unique insight into the underlying mechanism of the circuits, and that, consequent on this synthetizaton, the possibility now exists to study circuits' mechanism without impairing cellular functions.

However, such insights into underlying mechanisms cannot explain why certain kinds of biological behavior can occur only under certain sets of precise conditions, and why extrapolative and intuitive expectations based upon very exact (non-quantitative) descriptions do not suffice to accurately predict such conditional behaviors. For instance, cytosolic Ca2+ oscillations of the cellular rhythms [2,3] category "are triggered in various types of cell by treatment with a hormone or neurotransmitter.

" (Science Week, 1997) contrary to speculative expectations of such outcomes as dissimilar, perhaps non-cytosolic Ca2+ oscillations. Again, in the generation of oscillations in models based on negative feedbacks: While extrapolative or intuitive explanations can readily offer reasons for the spontaneous generation of oscillations by negative feedback, they will omit a lot of essential information because they will fail "to explain why oscillations only occur in precise conditions, which critically affect both the degree of cooperativity of repression and the delay in the negative feedback loop." (ibid). Consequently, a justification emerges for the exploration of the possibility of developing large-scale quantitative dynamic cell simulations towards a holistic- qualitative and quantitative- appreciation of complex biological pathways.

Such large-scale systems, with the powerful and flexible simulations of an E-cell system, will permit the development of comprehensive metabolical maps, elucidatory models that will not only encompass all cellular components and all the gene-and-protein regulatory networks of the biological pathway under consideration, but will allow for a precise determination of why specific genetic manifestations occur under given set(s) of conditions. I should, therefore, like to research the possibility of developing such powerful metabolic models as will simulate not only complex biochemical genetic circuits but also the effects of the environmental influences: static-cum-dynamic simulating models that will allow for both computational and qualitative analysis of biological pathways.

The success of this research will facilitate the appreciation of genetic circuits and gene-and-protein regulatory networks. The dynamic component of the comprehensive model will address dynamic riddles of gene-and-protein regulatory circuits while the static component will answer the need for quantitative and computational analyses toward a better appreciation of correlations amongst the biological pathway parameters of the circuits. Reference ListGoldbeter, A.

Biochemical Oscillations and Cellular Rhythms. Cambridge: Cambridge Univ. Press, 1996.Goldbeter, A. Computational approaches to cellular rhythms. Nature 420. Cambridge: Cambridge Univ. Press, 1996. 2002 pp 238-245."ScienceWeek Crossing Barriers Since 1997." Systems Biology: on reconstruction of genetic circuits. , February 26, 2006