Serial femtosecond crystallography is the process for which an ultrafast free-electron x-ray laser diffracts a protein crystal into its atomic structural basis. From these atomic structures, scientists can better understand the functions of the diffracted proteins. This is important because the protein structures obtained from this process can also provide valuable information that can help redesign medicinal drugs that will target diseases caused by certain proteins. One of the objectives for this research project is to work with a computational crystallography toolbox (CCBTX) that is still in development towards becoming an automated data analyzing software. We collect data by manually running the built in programs on python and analyzing the outputs given through a variety of parameters for commands such as averaging dark images and masking out bad pixels. This helps determine the efficiency of the built in software of the computational crystallography toolbox. Another objective was to use mathematical theory to calculate the sigma level of an automated peak finding threshold on a given peak value. Further more, we calculated the the probability of obtaining the peak value desired and verified the accuracy of the mathematical derivation through a python simulation on Jupyter Notebook.


Richard Partridge and Noah Kurinsky

Lab site

SLAC National Accelerator Laboratory (SLAC)

Funding Acknowledgement

This material is based upon work supported by the National Science Foundation through the Robert Noyce Teacher Scholarship Program under Grant # 1340110. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The research was also made possible by the California State University STEM Teacher and Researcher Program, in partnership with Chevron (www.chevron.com), the National Marine Sanctuary Foundation (www.marinesanctuary.org) and SLAC National Accelerator Laboratory.



URL: https://digitalcommons.calpoly.edu/star/465


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