Glad to clarify!
Also, note that whilst the "springs between atoms" analogy is nice for visualisation purposes, and certainly helps to initially explain the concept, it is not technically correct. Certainly, a similar analogy would be appropriate for external restraints and NCS local restraints, but not for jelly-body restraints.
In the case of jelly-body, applying "springs between atoms" (i.e. altering the likelihood function) would effectively slow refinement, thus requiring more cycles in order to reach convergence. Consequently, only the second derivative is altered, and the "springs between atoms" are not actually applied. This helps to stabilise refinement (purely because it is a regulariser and thus helps robustness to noise) without overly impeding speed of convergence. Still, many cycles may be required…
Cheers
Rob
On 23 Aug 2012, at 19:44, Robert Nicholls wrote:
> Hi Roger,
>
> You are correct, that *conceptually* the contribution to the target function is sum(w (|d|-|dcurrent|)^2)… however this is not actually applied to the target function. The target function remains unchanged. Only the 2nd derivative is affected by the jelly-body restraints.
>
> Also, note that the refmac5 ccp4i interface quotes: "use jelly body refinement with sigma 0.02". You mention that "bigger w, more rigid jellyfish". This is correct. However, note that w is inversely related to sigma, thus it should be acknowledged that "smaller sigma, more rigid jellyfish"…
>
> Also, note that the utility of such regularisers is greater when the effective observation-to-parameter ratio is worse, i.e. at lower resolutions. At this stage, it is not certain exactly what the resolution threshold is such that jelly-body restraints are useful. I can envisage that it not only depends on the resolution, but also on the quality (or noisiness) of the data. I am sure that there are 2.9A datasets out there that would benefit from such regularisers.
>
> Cheers
> Rob
>
>
>
> On 23 Aug 2012, at 19:31, Roger Rowlett wrote:
>
>> Garib gave a nice description of jelly-body refinement at the ACA meeting. IIRC from his talk, conceptually jelly-body refinment is the equivalent of adding "springs" between atoms within a certain radius of each other that restrain their movement during refinement. The restraints contribute to the target function curvature. The weight factor describes the contribution of the restraints to the overall target function. If w=1 and and the radius of atoms considered was infinity, you would have rigid body refinment. If w=0 you have normal uncontrained refinment. The REFMAC defaults are 4.2 A for the constraints radius, and 0.02 for the weighting factor. If I understand it correctly, it's basically like a slightly flexible rigid body refinement. Bigger w, more rigid jellyfish. (Someone will correct me if I have this wrong.)
>>
>> Mathematically, the contribution to the target function is sum(w (|d|-|dcurrent|)^2) where is d is a measure of the distances between atom pairs within a certain radius. The value d is the new distances and dcurrent is the old distances. The value w is the weighting factor.
>>
>> I have a recently obtained 2.9A dataset for which this approach might be interesting to try and see how it works compared to the usual unrestrained refinement and/or TLS, etc.
>>
>> Cheers,
>>
>> _______________________________________
>> Roger S. Rowlett
>> Gordon & Dorothy Kline Professor
>> Department of Chemistry
>> Colgate University
>> 13 Oak Drive
>> Hamilton, NY 13346
>>
>> tel: (315)-228-7245
>> ofc: (315)-228-7395
>> fax: (315)-228-7935
>> email: [log in to unmask]
>>
>> On 8/23/2012 1:27 PM, Nathan Pollock wrote:
>>> Dear experts,
>>>
>>> Could someone explain what it is exactly that jelly body refinement
>>> does? I think that I understand it intuitively but want to make sure.
>>> In the same vein, what does jelly body refinement sigma parameter
>>> control? I.e., in comparison to the default sigma = 0.02, does sigma =
>>> 0.1 make body more or less like a jelly fish?
>>>
>>> Thanks!
>>>
>>> - Nate
>
|