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EBS will accelerate much more than electrons only, the serial synchrotron crystallography needs to evolve

QUICK INFORMATION
Type
Seminar
Start Date
12-10-2018 13:30
End Date
12-10-2018 14:30
Location
Room 337, Central Building
Speaker's name
Nicolas Foos
Speaker's institute
ESRF
Contact name
Eva Jahn
Host name
Max NANAO
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Recent developments in hardware and software create opportunities for completely new approach in structural biology. Projects where crystallization of big mono crystal was a limitation can now go a step further thanks to the serial approach. Moreover, study biochemical process in time resolve benefits of an increasing interest. These profound changes in the paradigm of structural biology made the collection of serial synchrotron crystallography (SSX) data routine. Synchrotron has to propose in the same time innovations to the users and efficient solutions for the data management. Serial approach creates new type of data which require new methods for processing, merging and also for storage. The way the experiment is considered should be extended from the data-collection to the structure solution, in other word viewing the final result as a part of the service. The data management remains a significant challenge to the mainstream adoption of SSX.

One major challenge in the data processing within the serial approach is to find the best merging solution. To overcome this difficulty, we have developed an optimization strategy based on evolutionary principles. We show that the selection of sub-data sets for merging using a Genetic Algorithm (GA) provides an efficient method for obtaining complete, high quality merged datasets for both molecular replacement and anomalous phasing. Finally, we show that modifying the GA target function can even be used to segregate derivatized and native sub-datasets, which can then be used for a single loop SIR phasing experiment.

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