20.181:hw11 sols: Difference between revisions
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There is only one way to combine the given data so as to produce our desired units: | There is only one way to combine the given data so as to produce our desired units: | ||
<math>\frac{1\times10^9}{M\cdot sec}\cdot \frac{1 \mbox{ } mole}{6.023\times10^{23}} \cdot \frac{1}{1 \times 10^{-15} \mbox{ } L} = 1.66 \mbox{ } sec^{-1}</math> | |||
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Part 3: | |||
[[Image:Pa and pb vs time.jpg]] | |||
Observe above a "switching event," where pA and pB "switch" steady states. Note that neither the original abundances of pA nor pB are steady state values - the proteins settle into their steady states towards the end of the simulation. | |||
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Part 4: | |||
See above :) |
Latest revision as of 16:43, 11 December 2006
Solutions to HW 11
Part 1:
To complete the code shell provided, you had to insert something like the following code snippet:
tau_new = (a_i_old[rxn] / (a_i_new[rxn]+eps)) * (tau_i[rxn] - t_cur) + t_cur tau_i[rxn] = tau_new a_i_old[rxn] = a_i_new[rxn]
note that you can't update a_i until after you've calculated a new tau.
Part 2:
An easy way to solve this question is with dimensional analysis. If you've never heard of dimensional analysis before, it's essentially a fancy way of saying: manipulate the data to produce a value with the correct units; more often than not, this value will also be the correct quantity.
For instance, we know that we're trying to calculate the probability per unit time that a particle collision causes a reaction. Our solution should therefore be in units of [1/time] (probabilities are unitless!).
There is only one way to combine the given data so as to produce our desired units:
[math]\displaystyle{ \frac{1\times10^9}{M\cdot sec}\cdot \frac{1 \mbox{ } mole}{6.023\times10^{23}} \cdot \frac{1}{1 \times 10^{-15} \mbox{ } L} = 1.66 \mbox{ } sec^{-1} }[/math]
Part 3:
Observe above a "switching event," where pA and pB "switch" steady states. Note that neither the original abundances of pA nor pB are steady state values - the proteins settle into their steady states towards the end of the simulation.
Part 4:
See above :)