Statistical Analysis and Modelling of Crystallization Outcomes

• Published in: Journal of applied crystallography Vol. 30; no. 4; pp. 502 - 506
• Main Authors: Sedzik, J., Norinder, U.
• Format: Journal Article
• Language: English
• Published: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01-08-1997; Blackwell
• Subjects: Cross-disciplinary physics: materials science; rheology; Exact sciences and technology; Materials science; Methods of crystal growth; physics of crystal growth; Physics; Theory and models of crystal growth; physics of crystal growth, crystal morphology and orientation; Crystal growth; Proteins; Experimental result; Statistical analysis; Variable; Theoretical study; Regression analysis; Least square fit
• ISSN: 1600-5767; 0021-8898; 1600-5767
• DOI: 10.1107/S0021889897001945

This work describes a novel application of a recently developed statistical partial least‐squares regression technique for the problem of establishing relationships between experimental variables in crystallization trials and the experimental results. To validate this method published sets of factorially designed crystallization trials were analyzed and it was discovered that these derived models show very good predictivity. These mathematical constructs cannot explain the detailed mechanism of crystallization, but are a pragmatic and powerful tool which enables the crystal growers to set up crystallization trials not only in a rational manner but also with confidence. This is a useful and a general methodological approach particularly when crystallizing proteins of limited supply.