This unique text reference presents an overview of the computational aspects of protein
crystallization describing how to build robotic high-throughput and crystallization analysis
systems. The coverage encompasses the complete data analysis cycle including the set-up of
screens by analyzing prior crystallization trials the classification of crystallization trial
images by effective feature extraction the analysis of crystal growth in time series images
the segmentation of crystal regions in images the application of focal stacking methods for
crystallization images and the visualization of trials.Topics and features: describes the
fundamentals of protein crystallization and the scoring and categorization of crystallization
image trials introduces a selection of computational methods for protein crystallization
screening and the hardware and software architecture for a basic high-throughput system
presents an overview of the image features used in protein crystallization classification and
a spatio-temporal analysis of protein crystal growth examines focal stacking techniques to
avoid blurred crystallization images and different thresholding methods for binarization or
segmentation discusses visualization methods and software for protein crystallization analysis
and reviews alternative methods to X-ray diffraction for obtaining structural information
provides an overview of the current challenges and potential future trends in protein
crystallization.This interdisciplinary work serves as an essential reference on the
computational and data analytics components of protein crystallization for the structural
biology community in addition to computer scientists wishing to enter the field of protein
crystallization.
