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Scalability : a statistical mechanics perspective on gene regulation and expression. Alessandro Giuliani. Scalability: a refresher. A scalable system displays behaviours dependent on the presence of an ensemble and not directly derivable from microscopic properties of the single
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Scalability : a statistical mechanics perspective on gene regulation and expression Alessandro Giuliani
Scalability: a refresher A scalable system displays behaviours dependent on the presence of an ensemble and not directly derivable from microscopic properties of the single elements. A portion sufficiently large has the same properties of the whole system.
An highly connected system displays scalable properties if has the possibility of establishinglong range correlations
Local properties have a general originGeneral properties come from local correlations
At odds with a road map, in which the block of a road with an high capacity cannot be overcame by the deviation of traffic on a narrow road, metabolism seems to be only dependent of topology: no lethal purely kynetic mutants.
The citokyne response is the ‘local’ portion of the network response, that can be elicited only when Toll-like receptor system is active. The genome-wide scalable response is the ‘whole netowrk resonant’ response that is elicited even when Toll-like receptor system is out of work
The correlation computed on the entire profile of micro-RNA between progenitor (CD34) and different lineages decays monotonously in time. This behavior is exactly the same with a much smaller random set of probes: scalability !
step1 step2 step3 0,0552 0,0928 0,1619 e-mk 0,0678 0,1145 0,1537 e-g 0,0747 0,1269 0,1750 e-mo 0,0260 0,0653 0,1192 g-mk 0,0159 0,0496 0,0546 g-mo 0,0289 0,0808 0,1413 mo-mk
Conclusions: • Biological systems, at every observation scale, display a wide spectrum • of behaviours from the extreme specificity (local actions) to scalability (general • effects). • Network paradigm allows to rationalize both specificity and scalability in terms of • attacks to crucial nodes and fault tolerance to random errors. • 3. The single cell is not necessarily the place of ‘definitive explanations’ in biology. • Many macroscopic very reliable phenomena ask for a explanation at the • population level: ecology in a plate. • 4. The consideration of cell lines phenotypes as attractors of an high dimensional • systems asks for a different approach in pharmacological intervention with respect • to usual ‘target identification’ pharmacology.