I would like to ad a strategy that says: Max energy level i tetraloops allowed is 4,5. Anything above that should be penalized.
Dear Eli,
Your strategy has been added to our implementation queue with task id 28. You can check the schedule of the implementation here.
Unfortunately we are still having trouble with the energy calculation so we can’t specify exact ETA yet…we’ll try to fix the problem as soon as possible!
Thanks for sharing your idea!
EteRNA team
Hello Eli,
I’ve been assigned to help implement this strategy! I have a few initial questions

I’m guessing you mean 4.5 right? (Strategy says 4,5) Just making sure I’m not missing some sort of notation.

Do you have a basic idea of how you want it to be penalized? Our scripts return a score for each design on a scale of 0100, so would you want it to be 1 point per kCal above 4.5 in a linear fashion or something exponential, for example?
Thanks!
Hi Jerry!
Yes. I mean 4.5.
I would like to penalise with 1 pr. 0.1 energy level over 4.5. I didn’t think as far as linear or exponential. I’ll keep that in mind for future strategies I think i’ll pick linear here.
Good luck!
Thanks for your help Eli! The strategy should be out soon!
Dear Eli Fisker
We are glad to report that your strategy has been implemented and tested.
While implementing your strategy, we have made small changes to the parameters you specified to optimize the performance.
Note that we’ll always run a optimization over the parameters you specify, so you won’t have to worry about fine tuning all the numbers you use.
Just the idea and rough numbers are enough to run your algorithm!
Length : Your strategy was implmented with 14 line of code.
Ordering : We ran your strategy on all synthesized designs and ordered them based on predicted scores. The correlation of your strategy’s ordering with the ordering based on the actual scores was 0.132660505837. (1.0 is the best score, 1.0 is the worst score. A completely random prediction would have 0 correlation)
Please note that the numbers specified above will change in future as we’ll rerun your algorithm whenever new synthesis data is available.
More detailed result has been posted on the strategy market page. Thank you for sharing your idea, and we look forward to other brilliant strategies from you!