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David Minh, associate professor of chemistry, has been awarded a $240,000 grant from the National Science Foundation to pursue the development of statistical methods for studying molecular binding interactions.

Minh’s work includes a collaboration with Lulu Kang, associate professor of applied mathematics, and John Chodera from the Sloan Kettering Institute in New York.

Full understanding of these interactions requires integrating large amounts of data collected through the use of multiple analytical instruments and experimental protocols. Existing statistical methods and software do not fully integrate data from multiple sources to produce useful knowledge.

The research team is developing new methods and software to analyze chemical data from these multiple sources in relation to molecule binding. The software constructs Bayesian networks that consider sources of experimental error, performs Bayesian inference weighing evidence for competing physical models, obtains credible intervals for thermodynamic and kinetic parameters, and proposes new experiments.

The team will use this software to advance knowledge of cooperativity between binding sites.

David Minh, Lulu Kang, “CDS&E: Elucidating Binding using Bayesian Inference to Integrate Multiple Data Sources,” National Science Foundation ($240,000).