While I was working on making my entropy/switch strategy more specific, I started wondering. Do turnoff labs have higher entropy than turnon labs? And it really seems to be the case. So I’m splitting strategies after this feature.
Strategy
Turnoff switches (MS2 is turned off in state 2)
Give +2 to designs having entropy between 1 to 1.4
Give +3 to designs having entropy between 1.5 to 2.
Turn on switches (MS2 is turned on in state 2)
Give +3 for entropy between 1 to 1.4
Give +2 for entropy between 1.5 to 2
General
Give -2 to designs having entropy below 0.9.
Give + 1 and decrease to 0, to designs having entropy between 2.1 to 3
Penalize exponentially for anything having an entropy above 3
Thx to Pablo for pointing out the relation between medium high entropy and switches.
Background
This strategy will miss some of the good switches, as a few of them land in entropy area of solid static design or an entropy range that is not scored high. I’m assuming that then it is the folding algorithm that in these cases are not able to predict the right entropy. Since designs that usually fall out are the ones that the energy model deems unstable, so this may be a way to identify them, so they don’t get penalized to hell. Eg. perhaps turnoff entropy judgement in these cases.
Some of the other fallout winners that ends with an entropy in the area of static switches, are full moving switches.
So this strategy will not uncover all good switches, just cover a general good entropy range for most MS2/FMN switches. If designs land in rewarded area of entropy, it’s good. But it’s no guarantee they will also switch as wished for. Just its likely they actually do switch. :)
Original Author: Eli Fisker Original Link: https://getsatisfaction.com/eternagame/topics/-strategy-market-switch-entropy-in-ms2-aptamer-switches
Intro
While I was working on making my entropy/switch strategy more specific, I started wondering. Do turnoff labs have higher entropy than turnon labs? And it really seems to be the case. So I’m splitting strategies after this feature.
Strategy
Turnoff switches (MS2 is turned off in state 2) Give +2 to designs having entropy between 1 to 1.4 Give +3 to designs having entropy between 1.5 to 2.
Turn on switches (MS2 is turned on in state 2) Give +3 for entropy between 1 to 1.4 Give +2 for entropy between 1.5 to 2
General Give -2 to designs having entropy below 0.9. Give + 1 and decrease to 0, to designs having entropy between 2.1 to 3 Penalize exponentially for anything having an entropy above 3
Thx to Pablo for pointing out the relation between medium high entropy and switches.
Background
This strategy will miss some of the good switches, as a few of them land in entropy area of solid static design or an entropy range that is not scored high. I’m assuming that then it is the folding algorithm that in these cases are not able to predict the right entropy. Since designs that usually fall out are the ones that the energy model deems unstable, so this may be a way to identify them, so they don’t get penalized to hell. Eg. perhaps turnoff entropy judgement in these cases.
Some of the other fallout winners that ends with an entropy in the area of static switches, are full moving switches.
So this strategy will not uncover all good switches, just cover a general good entropy range for most MS2/FMN switches. If designs land in rewarded area of entropy, it’s good. But it’s no guarantee they will also switch as wished for. Just its likely they actually do switch. :)
Background articles
Switches and entropy
Part II - ROBOTS, REPEATS & ENTROPY
Entropy, RNA and free energy
Pablo’s lecture on RNA, entropy and free energy