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Graham, Daniel

Emeritus Professor

Education

  • B.S., 1976, Stanford University
  • Ph.D., 1981, Washington University, St. Louis
  • Postdoctoral Fellow, 1981-83, Boston University

Research Interests

My research interests lie in the application of information theory to thermodynamic systems, including molecules, an endeavor at the intersection of thermodynamics, probability and statistics, and computer science. While information theory was developed originally to understand—and thus improve—communication systems, it provides yet another powerful tool by which the relation between molecular structure and function can be comprehended.   My research is a search for new ways to predict molecular activity in advance of experiment, and to understand thermodynamic algorithms at the micro- and macroscopic scales.

My approach to the microscopic scale concentrates on the electronic messages transmitted by molecules during Brownian motion and collisions.  These messages are represented pictorially by structure diagrams combined with a simple random walk model.  Thermochemical principles are able to address the energetics of the messages; probability fundamentals enable the message information to be quantified and correlated.   Lastly, conceptuals drawn from computer science establish connections between the messages and their chemical effects.  Overall, the results are new quantitative structure/activity relations (QSARs) for organic compounds.  These are of significance to several disciplines including biological, medicinal, and industrial organic chemistry.

Publications/Research Listings

Chemical Thermodynamics and Information Theory with Applications. Daniel J. Graham. Taylor and Francis Group, CRC Press: Boca Raton, Florida, 2011.

The Analysis of Organic Reaction Pathways by Brownian Processing, in Statistical Modeling of Molecular Descriptors in QSAR/QSPR; Daniel J. Graham;  M. Dehmer, K. Varmuza, and D. Bonchev, editors. Wiley-Blackwell:Weinheim,Germany, 2012. 

 “On the Information Expressed in Enzyme Structure:  More Lessons from Ribonuclease A.”  Daniel J. Graham and Jessica L. Greminger.  Molecular Diversity 15, Number 3, 769 (2011). 

 “On the Information Expressed in Enzyme Primary Structure:  Lessons from Ribonuclease A.”  Daniel J. Graham and Jessica L. Greminger.  Molecular Diversity 2009 DOI 10.1007/s11030-009-9211-3. 

“Information and Classical Thermodynamic Transformations.” Daniel J. Graham and Miriam Kim.  Journal of Physical Chemistry B 112, 10585 (2008).

*"Information Content in Organic Molecules:  Brownian Processing at Low Levels." Daniel J. Graham. Journal of Chemical Information and Modeling 47, 376 (2007). 

*"Information Content and Organic Molecules: Aggregation States and Solvent Effects.” Daniel J. Graham. Journal of Chemical Information and Modeling 45, 1223 (2005).

*"Information Content In Organic Molecules:  Quantification and Statistical Structure Via Brownian Processing." Daniel J. Graham, Christopher Malarkey, and Matthew V. Schulmerich. Journal of Chemical Information and Computer Sciences 44, 1601 (2004).

*"Information Content In Organic Molecules:  Reaction Pathway Analysis Via Brownian Processing." Daniel J. Graham and Matthew V. Schulmerich. Journal of Chemical Information and Computer Sciences 44, 1612 (2004).