plot_score = (number of white cells in the upper triangle of the pairwise probabilities plot) / (total number of cells in the upper triangle of the pairwise probabilities plot)

cap_score = ((number of GC pairs that are at the end of a stack) + 0.5 * (number of GC pairs that are 1 away from the end of a stack)) / (3 * total number of stacks)

gc_penalty = 2 if 80% or more of the design’s pairs are GC pairs, 0 otherwise.

A design’s total score is: (2 + plot_score + cap_score - gc_penalty) * 25

The +2 and *25 are just to make it come out to between 0 and 100.

I want to apologize about the delays in implementing your strategy.

We are having technical problems in integrating dotplots to the strategy market right now…We’ll get back to your strategy as soon as we fix the problem!

We are glad to report that your strategy has been implemented and tested.

We also want to apologize the delay again. We had hard time getting the dotplot to work with the strategy market system.

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 70 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 0.379686489981. (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!