Data Analytics For Protein Crystallization (computational Biology)
by Marc L. Pusey /
2017 / English / PDF
4.9 MB Download
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.
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.
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.
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.
