[ccp4bb] Postdoctoral positions available in Duke-NUS, Singapore

[Sheemei Lok]

CryoEM post-doctoral positions are available at the Duke-NUS Graduate Medical 
School, Singapore. Duke-NUS Graduate Medical School is a global partnership 
between Duke University in the US and the National University of Singapore. Two 
post-doctoral positions with competitive salary packages are available at the 
laboratory of Shee-Mei Lok (http://www.loksheemeilab.com/) in the Emerging 
Infectious Disease program of the Duke-NUS.  Projects undertaken by the 
post-doc will lead to further understanding of the neutralization mechanism of 
various antiviral therapeutics against flavivirus/alphaviruses viruses. 
Individuals with experience in x-ray crystallography and/or cryoEM image 
reconstruction are highly desirable.Interested individuals should send their 
CV, experience, research interest, and a list of three referees to Dr Shee-mei 
Lok at this email:sheemei@duke-nus.edu.sg.  Regards, Shee-Mei LokAssociate 
Professor/National Research Foundation InvestigatorProgram in Emerging 
Infectious DiseasesDuke-NUS Medical SchoolKTP BuildingLevel 9 8 college 
RoadSingapore 169857Ph:65-65165840 Associate Professor/Principal 
InvestigatorCenter for BioImaging SciencesDepartment of Biological 
SciencesNational University of SingaporeSingapore 



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Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[Whitley, Matthew J]

For some reason, the September 19th ccp4bb digest got caught in my spam filter 
and didn't come through until a few minutes ago, so I didn't see several 
responses concerning interesting datasets for processing until just now.

Therefore, thanks also to Kay Diederichs, Eugene Osipov, and David Waterman for 
responding (and also to everyone else who responded if I am still overlooking 
anyone.)

As I mentioned before, I will be happy to compile a list of suggested datasets 
and make it available via this list.

Matthew


---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine



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[ccp4bb] Phenix version 1.14 released

[Paul Adams]

The Phenix developers are pleased to announce that version 1.14 of Phenix is 
now available (build 1.14-3260). Binary installers for Linux, Mac OSX, and 
Windows platforms, and the source installer, are available at the download site:

http://phenix-online.org/download/

Highlights for this version:

- Reorganization, updates and addition of cryo-EM tools:
  - phenix.mtriage - assess map and model quality 
  - phenix.auto_sharpen - map sharpening 
  - phenix.map_symmetry - identify symmetry in maps 
  - phenix.map_box - cut out unique parts of maps 
  - phenix.combine_focused_maps - combine different maps 
  - phenix.dock_in_map - automatically place an atomic model into a map 
  - phenix.map_to_model - automatically build atomic model from a map 
  - phenix.sequence_from_map - identify sequence from a map 
  - phenix.real_space_refine - improved refinement of models 
  - phenix.validation_cryoem - separate tool for comprehensive validation of 
models and maps

- phenix.cablam_idealization - Tool to automatically fix Cablam outliers

- eLBOW
  - better support for metals and metal clusters
  - added plugin for QM package Orca

- Phaser-2.8.2
  - bugfixes
- Phassade substructure search when starting from seed substructure
- fix crash in MR_ATOM
- problems with cumulative intensity distribution for extremely weak data
  - improve computation and presentation of data information content

- Performance improvements
  - NCS search
  - Generation of secondary structure restraints
  - Clashscore calculation
  - AmberPrep is more robust
  - Restraints for ARG improved

- New Phenix video tutorials

- GUI
  - New section in main window for cryo-EM tools
  - Separate validation GUI for cryo-EM structures
  - Added phenix.map_symmetry
  - Added phenix.dock_in_map
  - Added phenix.map_to_structure_factors
  - Added phenix.combine_focused_maps
  - Added phenix.sequence_from_map

- phenix.ligand_identification:
  - Added an option to generate ligand library based on sequence and structural
homologs of the input pdb model.

For a full list of changes see:

http://www.phenix-online.org/documentation/CHANGES

Please note that this publication should be used to cite use of Phenix:

PHENIX: a comprehensive Python-based system for macromolecular structure 
solution. P. D. Adams, P. V. Afonine, G. Bunkóczi, V. B. Chen, I. W. Davis, N. 
Echols, J. J. Headd, L.-W. Hung, G. J. Kapral, R. W. Grosse-Kunstleve, A. J. 
McCoy, N. W. Moriarty, R. Oeffner, R. J. Read, D. C. Richardson, J. S. 
Richardson, T. C. Terwilliger and P. H. Zwart. Acta Cryst. D66, 213-221 (2010).

Full documentation is available here:

http://www.phenix-online.org/documentation/

There is a Phenix bulletin board:

http://www.phenix-online.org/mailman/listinfo/phenixbb/

Please consult the installer README file or online documentation for 
installation instructions.

Direct questions and problem reports to the bulletin board or:

h...@phenix-online.org and b...@phenix-online.org

Commercial users interested in obtaining access to Phenix should visit the
Phenix website for information about the Phenix Industrial Consortium.

The development of Phenix is principally funded by the National Institute of
General Medical Sciences (NIH) under grant P01-GM063210. We also acknowledge
the generous support of the members of the Phenix Industrial Consortium.

-- 
Paul Adams
Division Director, Molecular Biophysics & Integrated Bioimaging, Lawrence 
Berkeley Lab
Division Deputy for Biosciences, Advanced Light Source, Lawrence Berkeley Lab
Adjunct Professor, Department of Bioengineering, U.C. Berkeley
Vice President for Technology, the Joint BioEnergy Institute
Laboratory Research Manager, ENIGMA Science Focus Area

Building 33, Room 347
Building 978, Room 4126
Tel: 1-510-486-4225, Fax: 1-510-486-5909
http://cci.lbl.gov/paul

Lawrence Berkeley Laboratory
1 Cyclotron Road
BLDG 33R0345
Berkeley, CA 94720, USA.

Executive Assistant: Louise Benvenue [ lbenve...@lbl.gov ][ 1-510-495-2506 ]
--



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Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[David Waterman]

Hi Matthew,

I'm a little late to the thread, but I thought I would still like to add
DPF3b, kindly provided by Wolfram Tempel. This dataset is available on
zenodo and forms the basis of a tutorial for using DIALS:
https://dials.github.io/documentation/tutorials/correcting_poor_initial_geometry_tutorial.html.
As the tutorial states,

This is a challenging dataset to process. There are a combination of
problems, including:

   - A ‘reversed’ rotation axis
   - Incorrect beam centre recorded in the image headers
   - Split spots
   - Multiple lattices
   - Systematically weak spots that may correspond to pseudocentring

Cheers
-- David


On Tue, 25 Sep 2018 at 18:27, Whitley, Matthew J  wrote:

> Dear colleagues,
>
> I want to thank the following people for providing suggestions and
> comments about ‘difficult’ datasets suitable for teaching data processing:
>
> Tim Craig
> Jacob Keller
> Graeme Winter
> Aleksandar Bijelic
> Clemens Vonrhein
> Loes Kroon-Batenburg
> James Holton
>
> If anyone else has suggestions for good datasets for teaching processing,
> I would still be happy to hear them.
>
> Finally, several people asked me to make available a list of all the
> dataset suggestions I receive.  I am happy to do so, and I will post a
> message to this list when the information is up and available, probably
> later in the fall.
>
>
> Sincerely,
> Matthew
>
>
>
> ---
> Matthew J. Whitley, Ph.D.
> Research Instructor
> Department of Pharmacology & Chemical Biology
> University of Pittsburgh School of Medicine
>
>
>
>
> On 9/19/2018 5:15 PM, Whitley, Matthew J wrote:
>
> Dear colleagues,
>
> For teaching purposes, I am looking for a small number (< 5) of
> macromolecular diffraction datasets (raw images) that might be
> considered 'difficult' for a beginning crystallography student to
> process.  By 'difficult' I generally mean not able to be processed
> automatically by a common processing package (XDS, Mosflm, DIALS, etc)
> using default settings, i.e., no black box "click and done" processing.
> The datasets I am looking for would have some stumbling block such as
> incorrect experimental parameters recorded in the image headers,
> multiple lattices that cause indexing to fail, datasets for which
> determining the correct space group is tricky, datasets for experiments
> in which the crystal slipped or moved in the beam, or anything else you
> can think of.  The idea is for these beginning students to examine
> several datasets that highlight various phenomena that can lead one
> astray during processing.
>
> A good candidate dataset would also ideally comprise a modest number of
> images so as to keep integration time to a minimum.  Factors that are
> mostly irrelevant for my purpose: resolution (as long as better than
> ~3.5 Å), source (home vs synchrotron), presence/absence of anomalous
> scattering,  presence/absence of ligands, monomeric vs oligomeric
> structures, etc.  Also, to be clear, I am not looking for datasets that
> have so many pathologies that they would require many long hours of work
> for an expert to process correctly.
>
> I have checked public repositories such as proteindiffraction.org and
> SBGrid databank, but all of the datasets I acquired from these sources
> process satisfactorily with little effort, and in any event I know of no
> way to search for 'challenging' datasets.  (I also wonder whether
> anybody is in the habit of depositing, shall we say, less-than-pristine
> images to public repositories?)
>
> If you know of such a dataset that is already publicly available, or if
> you have such a dataset that you are willing to share for solely
> educational purposes, I would appreciate hearing from you, either on- or
> off-list.
>
> Thank you in advance for your suggestions.
>
> Matthew
>
>
>
>
> --
>
> To unsubscribe from the CCP4BB list, click the following link:
> https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=CCP4BB=1
>



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Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[Whitley, Matthew J]

Dear colleagues,

I want to thank the following people for providing suggestions and comments 
about ‘difficult’ datasets suitable for teaching data processing:

Tim Craig
Jacob Keller
Graeme Winter
Aleksandar Bijelic
Clemens Vonrhein
Loes Kroon-Batenburg
James Holton

If anyone else has suggestions for good datasets for teaching processing, I 
would still be happy to hear them.

Finally, several people asked me to make available a list of all the dataset 
suggestions I receive.  I am happy to do so, and I will post a message to this 
list when the information is up and available, probably later in the fall.


Sincerely,
Matthew



---
Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine




On 9/19/2018 5:15 PM, Whitley, Matthew J wrote:
Dear colleagues,

For teaching purposes, I am looking for a small number (< 5) of
macromolecular diffraction datasets (raw images) that might be
considered 'difficult' for a beginning crystallography student to
process.  By 'difficult' I generally mean not able to be processed
automatically by a common processing package (XDS, Mosflm, DIALS, etc)
using default settings, i.e., no black box "click and done" processing.
The datasets I am looking for would have some stumbling block such as
incorrect experimental parameters recorded in the image headers,
multiple lattices that cause indexing to fail, datasets for which
determining the correct space group is tricky, datasets for experiments
in which the crystal slipped or moved in the beam, or anything else you
can think of.  The idea is for these beginning students to examine
several datasets that highlight various phenomena that can lead one
astray during processing.

A good candidate dataset would also ideally comprise a modest number of
images so as to keep integration time to a minimum.  Factors that are
mostly irrelevant for my purpose: resolution (as long as better than
~3.5 Å), source (home vs synchrotron), presence/absence of anomalous
scattering,  presence/absence of ligands, monomeric vs oligomeric
structures, etc.  Also, to be clear, I am not looking for datasets that
have so many pathologies that they would require many long hours of work
for an expert to process correctly.

I have checked public repositories such as 
proteindiffraction.org and
SBGrid databank, but all of the datasets I acquired from these sources
process satisfactorily with little effort, and in any event I know of no
way to search for 'challenging' datasets.  (I also wonder whether
anybody is in the habit of depositing, shall we say, less-than-pristine
images to public repositories?)

If you know of such a dataset that is already publicly available, or if
you have such a dataset that you are willing to share for solely
educational purposes, I would appreciate hearing from you, either on- or
off-list.

Thank you in advance for your suggestions.

Matthew






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[ccp4bb] ccp4 release 7.0 update 063

[Ballard, Charles (STFC,RAL,CSE)]

Dear All

update 063 is available containing

* ccp4i2
- integration of dials gui, lattice viewer, and molprobity validation

* dials gui
- updates for dials 1.10

* aimless
- update to 0.7.3

* dimple
- various bug fixes

* crank2
- 

* morda
- update to v24

Next update DIALS.

Charles

on behalf of the CCP4 core team and developers



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