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    Hi Arjen,<br>
    <br>
    thanks for pointing this out! I will have a look!<br>
    <br>
    Pavel<br>
    <br>
    <div class="moz-cite-prefix">On 9/13/16 08:06, arjen jakobi wrote:<br>
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cite="mid:CACTB1uMW3fW+5zL=Bb0bXzTfXR4aB4zhXAbq2Yz7qyNx_jy7qA@mail.gmail.com"
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          <div>Hi Oliver, <br>
            <br>
            indeed this can be beneficial. We have done this e.g. for a
            cryo-EM map of Pol III where for the apo models we see
            substantial resolution variation (doi:10.1038/nature16143;
            doi:10.1111/febs.13732).<br>
            <br>
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          Best,<br>
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        Arjen<br>
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      <div class="gmail_extra"><br>
        <div class="gmail_quote">On 13 September 2016 at 16:57, Oliver
          Clarke <span dir="ltr">&lt;<a moz-do-not-send="true"
              href="mailto:olibclarke@gmail.com" target="_blank">olibclarke@gmail.com</a>&gt;</span>
          wrote:<br>
          <blockquote class="gmail_quote" style="margin:0 0 0
            .8ex;border-left:1px #ccc solid;padding-left:1ex">Thanks
            Pavel!<br>
            <br>
            So just to be sure - the average weight obtained with the
            randomly selected fragments is used for the entire model? Or
            different weights are used for different regions? I guess
            the latter would be in some ways preferable for large
            structures in cryoEM where there is a substantial variation
            in local resolution?<br>
            <br>
            Cheers,<br>
            Oli<br>
            <div class="HOEnZb">
              <div class="h5">&gt; On Sep 13, 2016, at 10:54 AM, Pavel
                Afonine &lt;<a moz-do-not-send="true"
                  href="mailto:pafonine@lbl.gov">pafonine@lbl.gov</a>&gt;
                wrote:<br>
                &gt;<br>
                &gt; Hi Oliver,<br>
                &gt;<br>
                &gt; unlike reciprocal space refinement where
                optimization of the weight requires systematically
                trying full refinement (which is very slow unless you
                use many cpus), in real space this can be done very
                quickly and the speed does not depend on model or map
                size.<br>
                &gt; The weight calculation procedure implemented in
                phenix.real_space_refine includes splitting the model
                into ten randomly picked continues ten-residue long
                segments, and finding the best weight for each segment.
                The best weight is considered to be the one that results
                in a model possessing pre-defined bond and angle rms
                deviations and that has best model-to-map fit among all
                trial weights. The obtained array of weights is filtered
                for outliers and the average weight is calculated and
                used as the best weight.<br>
                &gt;<br>
                &gt; Parameters defining bond/angle rmsds as targets for
                weight optimization:<br>
                &gt;<br>
                &gt;    target_bonds_rmsd = 0.01<br>
                &gt;    target_angles_rmsd = 1.0<br>
                &gt;<br>
                &gt; Pavel<br>
                &gt;<br>
                &gt; On 9/12/16 14:14, Oliver Clarke wrote:<br>
                &gt;&gt; Hi all,<br>
                &gt;&gt;<br>
                &gt;&gt; How does phenix.real_space_refine deal with
                restraint weighting? Looking at the output of the
                program, I get the impression that it splits the model
                up into  different chunks, and alters weights locally
                based on some model/map correlation metric - is this the
                case (and are there more specific details available), or
                how does it work otherwise?<br>
                &gt;&gt;<br>
                &gt;&gt; Cheers,<br>
                &gt;&gt; Oliver.<br>
                &gt;<br>
                <br>
                <br>
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