Re: [modeller_usage] Lucky16: Ordered search across multiple models?
To: R K Belew <>
Subject: Re: [modeller_usage] Lucky16: Ordered search across multiple models?
From: Modeller Caretaker <>
Date: Thu, 10 Nov 2011 14:04:00 -0800
Cc:
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...