On 11/7/11 2:31 PM, R K Belew wrote: > Suppose i run N independently seeded runs from the same alignment and > generate K models each time; ie, i have a distribution of N * K models. > Now consider a small fraction EPSILON of these with good GA341 > scores. i would expect the fraction of models which happened to > be model "target.B ..._k" ( ie, the model that gets generated the > k-th time by Modeller) to be uniform over choice of k, wouldn't you?
Yes, I would expect that.
> what makes model#16 so consistently good?
That is rather puzzling, since Modeller doesn't know how to generate "good" models (if it did, it would do it every time, not only for model #16!) All it can do is try to build models that violate the restraints as minimally as possible. The only difference between model #15 and model #16 is the starting conformation (the restraints and optimization are the same) but since that is generated randomly (by default) there shouldn't be any difference in the final statistics. I would suspect a bug in your procedure somewhere...
Ben Webb, Modeller Caretaker