Boolean model: each protein can either be present or absent. The interaction network can be encoded with a set of boolean functions exhibiting steady states.
- Gabriele Sales
Previous work: some nodes behave stochastically.
- Gabriele Sales
With SIN (stochasticity in nodes), they had an example of stochastic cellular differentiation. You understand what the probabilities are in SIN by looking at a population of cells.
- Allyson Lister
Example: stochasticity introduces cellular differentiation into a popolation.
- Gabriele Sales
The SIN method overrepresents noise in the system.
- Allyson Lister
This work employs a different approach: stochasticity in functions. The boolean function itself becomes noisy.
- Gabriele Sales
Advantage of this approach: the noise can be selected depending on the biological function it applies to.
- Gabriele Sales
Measure of robustness: probability of a steady state returning back to itself in the presence of internal pertubations (or faults).
- Allyson Lister
Once you start introducing faults, the robustness is much lower the more faults you add for SIN, but the robustness is only marginally lower using SIF.
- Allyson Lister
In SIN, 3 faults are sufficient to make all the states go into each other (results for the T-cell activation network).
- Gabriele Sales
Nice to "see" you here @Gabriele - it's good to have more than one person commenting :)
- Allyson Lister
@Allyson: I think this is getting addictive ;-)
- Gabriele Sales
@Gabriele - yes it is - just make sure you control it, and not the other way around! ;) But seriously, if a person is going to take notes anyway, why not take them in a way that 1) other people can see them, and 2) is nicely indexed and searchable ...
- Allyson Lister