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Data Analytics for Protein Crystallization pp 21–32Cite as

Scoring and Phases of Crystallization

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Part of the book series: Computational Biology ((COBO,volume 25))

Abstract

The practice of scoring of protein crystallization screening results is more honored in the breach than in the observance. However, as we hope to show in the balance of this treatise, it can lead to a means for extracting more information than immediately apparent from a crystallization experiment. Scoring has advantages beyond simple good scientific note-keeping practice; the act of objectively examining one’s results, with some thought added, can lead to a deeper appreciation of what led to those results, be it at the protein, screening solution, or mechanics of setting up the plate level. The first goal is to have a system which reflects an increase in the desirability of the results obtained with the numerical score. The scoring scale does not have to be complex or extensive; a 10-point scale is elaborated on herein. However, the scale should clearly distinguish between classes of desirable outcomes.

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Authors and Affiliations

  1. iXpressGenes, Inc., Huntsville, AL, USA

    Marc L. Pusey

  2. University of Alabama in Huntsville, Huntsville, AL, USA

    Ramazan Savaş Aygün

Authors
  1. Marc L. Pusey
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  2. Ramazan Savaş Aygün
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Correspondence to Marc L. Pusey .

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Pusey, M.L., Aygün, R.S. (2017). Scoring and Phases of Crystallization. In: Data Analytics for Protein Crystallization. Computational Biology, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-58937-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-58937-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58936-7

  • Online ISBN: 978-3-319-58937-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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