Hi Pavel, Actually, when we defined the MLI target (originally called MLF2: Pannu & Read, 1996), we did two tests where we compared R-factors (computed with the same set of F values) and phase errors (measured with the mean cosine of the phase error). In one case (Streptomyces griseus trypsin, where the bovine trypsin starting model was a very poor model) the difference was very small, but in the other case (Trypanosoma brucei GAPDH) the MLI target gave significantly better results. I'm not sure why you say that you couldn't use R-factors (though I prefer phase errors or map correlations). You could argue that R-factors computed using F should be biased to give better results to a target based on F than on I, but that wasn't a problem in our tests. Clearly there's room for more exhaustive tests, but that initial result demonstrated the theoretical advantage mentioned by Keitaro (accounting for negative net intensities) plus the advantage that it's a better approximation to an ideal likelihood target (measurement errors are closer to Gaussian in measured intensities than to Gaussian in amplitudes -- assumed in our MLF target -- or complex Gaussian in complex structure factors -- assumed in the Rice likelihood target). It would also be good to bring the Rice likelihood target into the tests. Regards, Randy On 1 Mar 2011, at 01:31, Pavel Afonine wrote:
Hi Keitaro,
A little off-topic, but will phenix implement MLI (maximum likelihood intensity target)?
eventually. The formulas are there, someone just needs to get enough of motivation to spend a couple of days and code them thus making available in phenix.refine. Once this is done, then there will be another set of troubles to deal with: - what to use to compute R-factors: Iobs or Fobs? If Fobs, then in turn you will go back to the original problem of converting I to F. If Iobs, then I bet a number of people will scream that they want to see the R-factors computed the "usual way" (using Fobs, that is). - Same questions about computing the maps.
I heard that MLI target gives a good result because MLI handles negative intensities naturally.
"Good" compared to what? How you evaluate that one is better than the other in this case? Obviosuly, you wouldn't be able to use the R-fators as the criteria. I guess I know how, but I'm not aware that anyone has ever done it (another little project for someone enthusiastic).
Overall, I conclude quoting one of my favorite papers:
"The choice of refinement against F**2 or F has generated more discussions than it probably warrants. (...)"
David Watkin "Structure refinement: some background theory and practical strategies" J. Appl. Cryst. (2008). 41, 491–522
All the best! Pavel.
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------ Randy J. Read Department of Haematology, University of Cambridge Cambridge Institute for Medical Research Tel: + 44 1223 336500 Wellcome Trust/MRC Building Fax: + 44 1223 336827 Hills Road E-mail: [email protected] Cambridge CB2 0XY, U.K. www-structmed.cimr.cam.ac.uk