Re: [ccp4bb] Vacuum pump in cold room
use the brand of vacuum pump without oil 发自网易邮箱大师 在2017年10月29日 01:17，Denis Rousseau 写道： Does anyone have experience with a vacuum pump in cold room? We have been told they may not start because of the viscosity of the oil? Thanks Denis Rousseau From: CCP4 bulletin board [CCP4BB@JISCMAIL.AC.UK] on behalf of Schulz, Eike-Christian [eike.sch...@mpsd.mpg.de] Sent: Friday, October 27, 2017 4:31 PM To:CCP4BB@JISCMAIL.AC.UK Subject: [ccp4bb] using CC1/2 to define resolution limit in Xscale Dear all, I would like to compare > 15 datasets and would like to use a common CC1/2 value as an objective criterion to determine the resolution cut-off. All data were integrated in XDS. Is there a convenient way to apply this in XSCALE or in any of its alternatives? With best regards, Eike
Re: [ccp4bb] Vacuum pump in cold room
Does anyone have experience with a vacuum pump in cold room? We have been told they may not start because of the viscosity of the oil? Thanks Denis Rousseau From: CCP4 bulletin board [CCP4BB@JISCMAIL.AC.UK] on behalf of Schulz, Eike-Christian [eike.sch...@mpsd.mpg.de] Sent: Friday, October 27, 2017 4:31 PM To: CCP4BB@JISCMAIL.AC.UK Subject: [ccp4bb] using CC1/2 to define resolution limit in Xscale Dear all, I would like to compare > 15 datasets and would like to use a common CC1/2 value as an objective criterion to determine the resolution cut-off. All data were integrated in XDS. Is there a convenient way to apply this in XSCALE or in any of its alternatives? With best regards, Eike
Re: [ccp4bb] using CC1/2 to define resolution limit in Xscale
I'd like to comment on Kay's statement, "People using a cutoff of 2 (or 3, or 1) for the mean I/sigI are just using an arbitrary number, as if it were magic." That may be true for values of 1 or 3, but 45 years ago, I was told by Lyle Jensen why a 2sigma(I) cutoff was appropriate. When people obtained reflection intensities from photographic film, some of the reflections were "unobserved" because they were below the cloudiness of the film. When diffractometers came into use with scintillation counters, measurements could be made for all reflections. So, if you had a refined structure based on photographic data, how could you compare it and its data set obtained from a diffractometer? It was determined that a 2sigma(I) cutoff corresponded to the "unobserved" level from film data. I don't know how quantitative this determination was, but it wasn't exactly "arbitrary". Ron On Sat, 28 Oct 2017, Kay Diederichs wrote: The ideas was to cut all datasets at say 30% CC1/2 to see how they differ in resolution I/sigI etc. for that given CC1/2 … not sure which insight that would give you. CC1/2 and mean I/sigI of the merged data are related quantities; that relation is given in (1). The formula given in "Box 1" of that paper shows that a CC1/2 of 20% corresponds to an average I/sigI of the merged data around 1, and 30% corresponds to about 1.3 . The advantage of CC1/2 over mean I/sigI is that the sigmas are not required. Sigmas are difficult to get right, or even consistent, and different programs result in different sigmas for the same data. Furthermore, correlation coefficients have known statistical properties, e.g. their "significance" (the probability of a given value, or higher, arising by chance) can be calculated. If that "significance" has a low numerical value (e.g. 0.1%) then you may conclude that this value is due to signal in your data. In this example, only in (statistically) 1 out of 1000 cases you would _wrongly_ conclude that there is signal. Whether a correlation coefficient is significant at a given "significance level" (e.g. 0.1% which is the value that results in a "*" appended to the numerical value in CORRECT.LP and XSCALE.LP) depends on its numerical value, and the number of unique reflections it is based upon. There is thus no fixed cutoff. BTW no such insight is available for the mean I/sigI of the merged data. People using a cutoff of 2 (or 3, or 1) for the mean I/sigI are just using an arbitrary number, as if it were magic. As long as it is "significant", the same goes for a CC1/2 cutoff of 20% or 30% or ... it is arbitrary. CC1/2 = 14.3% is the value where the correlation of the merged intensities with the (unknown) true intensities can be expected to be 50% - this is just to put the numbers into perspective, and is not to be used as a cutoff. For refinement, there is no "best" cutoff that always works. It depends on the accuracy of the model whether it can extract information from the weak intensities in the high-resolution data. There is a useful test called "paired refinement" that helps finding out if the weak data really improve the model, or not. It is rather simple to apply that test (PDB_REDO does it in an automated way) but its outcome depends on both the accuracy of the data, and the accuracy of the model. It is safe to err on the side of "too optimistic" high-resolution cutoff because there is no degradation of the model when using those data. But to cut "too low" may mean missing the opportunity to get a better model. One insight (Garib Murshudov) is that if the R/Rfree of your model in the high-resolution shell is >42% (assuming no twinning or tNCS) then that matches what would be obtained by refinement of the correct model against constant intensities (as derived from the Wilson plot) - an indication that one should rather not use the data beyond this resolution for refinement, or that the model has significant errors. Hope this helps, Kay (1) Karplus, P.A., Diederichs, K. (2015) Assessing and maximizing data quality in macromolecular crystallography. Curr. Opin. Struct. Biol. 34, 60-68; online at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4684713
Re: [ccp4bb] using CC1/2 to define resolution limit in Xscale
> The ideas was to cut all datasets at say 30% CC1/2 to see how they differ in > resolution I/sigI etc. for that given CC1/2 … not sure which insight that would give you. CC1/2 and mean I/sigI of the merged data are related quantities; that relation is given in (1). The formula given in "Box 1" of that paper shows that a CC1/2 of 20% corresponds to an average I/sigI of the merged data around 1, and 30% corresponds to about 1.3 . The advantage of CC1/2 over mean I/sigI is that the sigmas are not required. Sigmas are difficult to get right, or even consistent, and different programs result in different sigmas for the same data. Furthermore, correlation coefficients have known statistical properties, e.g. their "significance" (the probability of a given value, or higher, arising by chance) can be calculated. If that "significance" has a low numerical value (e.g. 0.1%) then you may conclude that this value is due to signal in your data. In this example, only in (statistically) 1 out of 1000 cases you would _wrongly_ conclude that there is signal. Whether a correlation coefficient is significant at a given "significance level" (e.g. 0.1% which is the value that results in a "*" appended to the numerical value in CORRECT.LP and XSCALE.LP) depends on its numerical value, and the number of unique reflections it is based upon. There is thus no fixed cutoff. BTW no such insight is available for the mean I/sigI of the merged data. People using a cutoff of 2 (or 3, or 1) for the mean I/sigI are just using an arbitrary number, as if it were magic. As long as it is "significant", the same goes for a CC1/2 cutoff of 20% or 30% or ... it is arbitrary. CC1/2 = 14.3% is the value where the correlation of the merged intensities with the (unknown) true intensities can be expected to be 50% - this is just to put the numbers into perspective, and is not to be used as a cutoff. For refinement, there is no "best" cutoff that always works. It depends on the accuracy of the model whether it can extract information from the weak intensities in the high-resolution data. There is a useful test called "paired refinement" that helps finding out if the weak data really improve the model, or not. It is rather simple to apply that test (PDB_REDO does it in an automated way) but its outcome depends on both the accuracy of the data, and the accuracy of the model. It is safe to err on the side of "too optimistic" high-resolution cutoff because there is no degradation of the model when using those data. But to cut "too low" may mean missing the opportunity to get a better model. One insight (Garib Murshudov) is that if the R/Rfree of your model in the high-resolution shell is >42% (assuming no twinning or tNCS) then that matches what would be obtained by refinement of the correct model against constant intensities (as derived from the Wilson plot) - an indication that one should rather not use the data beyond this resolution for refinement, or that the model has significant errors. Hope this helps, Kay (1) Karplus, P.A., Diederichs, K. (2015) Assessing and maximizing data quality in macromolecular crystallography. Curr. Opin. Struct. Biol. 34, 60-68; online at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4684713
[ccp4bb] Two openings for postdoctoral fellows at Berkeley National Lab
We are looking for two postdoctoral fellows to work on methods development for time resolved structural and spectroscopic studies on enzymes using X-rays, especially X-ray free electron lasers (XFELs). The fellows will work in the Kern/Yachandra/Yano group (http://www2.lbl.gov/vkyachan/ and http://biosciences.lbl.gov/profiles/jan-florian-kern/) at Berkeley Lab’s Molecular Biophysics & Integrated Bioimaging Division. We have been conducting a number of XFEL experiments on several different systems and some recent publications include: Fuller et al, Nature Methods 2017 http://www.nature.com/nmeth/journal/v14/n4/abs/nmeth.4195.html Young et al Nature 2016 https://www.nature.com/nature/journal/v540/n7633/full/nature20161.html Sierra et al Nature Methods 2016 https://www.nature.com/nmeth/journal/v13/n1/full/nmeth.3667.html Kern et al Nature Communications 2014 https://www.nature.com/articles/ncomms5371 Ideally the candidates should have a good background in one or more of the following fields: - Macromolecular crystallography - Microfluidics or stopped-flow instrumentation and application to enzyme studies. - X-ray spectroscopy of dilute transition metal systems/biological systems. - Designing of experimental setups for use at synchrotron/X-ray free laser facilities. - Electrochemistry of redox active enzymes. Details of the position and instructions how to apply can be found here: http://m.rfer.us/LBL0.x31 For informal inquiries please feel free to contact me: jfk...@lbl.gov Thanks, Jan Kern Jan Kern Research Scientist Molecular Biophysics and Integrated Bioimaging Division Lawrence Berkeley National Laboratory One Cyclotron Road, MS 66-327 Berkeley, CA 94720 USA phone: 510-486-4330 / -7437 e-mail: jfk...@lbl.gov
