Overview
- Presents an overview of computational aspects of protein crystallization
- Reviews computational methods for protein crystallization screening
- Discusses the effective scoring of protein crystallization trial images
- Examines the image processing of crystallization trial images
- Describes the spatiotemporal analysis of protein crystal growth
- Includes supplementary material: sn.pub/extras
Part of the book series: Computational Biology (COBO, volume 25)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Authors and Affiliations
About the authors
Dr. Ramazan S. Aygün is an Associate Professor in the Computer Science Department of the University of Alabama in Huntsville, USA.
Bibliographic Information
Book Title: Data Analytics for Protein Crystallization
Authors: Marc L. Pusey, Ramazan Savaş Aygün
Series Title: Computational Biology
DOI: https://doi.org/10.1007/978-3-319-58937-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-58936-7Published: 13 December 2017
Softcover ISBN: 978-3-319-86514-0Published: 30 August 2018
eBook ISBN: 978-3-319-58937-4Published: 27 November 2017
Series ISSN: 1568-2684
Series E-ISSN: 2662-2432
Edition Number: 1
Number of Pages: XX, 231
Number of Illustrations: 10 b/w illustrations, 56 illustrations in colour
Topics: Computational Biology/Bioinformatics, Data Mining and Knowledge Discovery, Image Processing and Computer Vision, Molecular Medicine, Biotechnology