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Updated: Dec 28, 2025

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
Published on: March 22, 2019
PyMDA: microcrystal data assembly using Python
Lina Takemaru1, Gongrui Guo1,2, Ping Zhu1
1Biology Department, Brookhaven National Laboratory, Upton, NY 11973, USA.
Abstract:
The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal and with unit-cell variations. A multi-stage data assembly method has previously been designed for microcrystal synchrotron crystallography. Here the strategy has been implemented as a Python program for microcrystal data assembly (PyMDA). PyMDA optimizes microcrystal data quality including weak anomalous signals through iterative crystal and frame rejections. Beyond microcrystals, PyMDA may be applicable for assembling data sets from larger crystals for improved data quality.
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