Abstract
This book provides the lifecycle of data analytics for protein crystallization. A wide range of topics starting from setting up screens to identifying macromolecular structure has been covered. In earlier chapters, the status-of-art and effective low-cost and real-time techniques for protein crystallization analysis have been provided. This chapter provides some of the challenges and future directions for protein crystallization.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Pusey, M.L., Aygün, R.S. (2017). Future of Computational Protein Crystallization. In: Data Analytics for Protein Crystallization. Computational Biology, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-58937-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-58937-4_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-58936-7
Online ISBN: 978-3-319-58937-4
eBook Packages: Computer ScienceComputer Science (R0)