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Hi all, Anthony Duff wrote (regarding R-fac and R-free from mapfiles?) > 2. CNS does a worse job of refining a structure in the late stages, even > accounting for differences in default restraint weights. (I don't know why > this would be so, with both using maximum likelihood... maybe the CNS algorithms are inferior?) This reminded me of a question I've been wondering about for a bit: Does maximum likelihood refer to a scoring function (generate gradients to optimize while refining), or both a scoring function and refinement menthod? As far as I understand, it's the first (based on what I've seen of poking around in the internals of programs that do ML refinement vs other types of refinement). But least-squares is a special case of maximum likelihood, and least-squares (again as far as I know) is both a scoring function and refinement method. Could somebody more knowledgable about maximum likelihood clear this up? Thanks, Pete Pete Meyer Fu Lab BMCB grad student Cornell University
