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Information Theory and Cell/Nanoparticle Modeling

By Peter J. Ortoleva

Indiana University

Published on


Physico-chemical models of cells and nanoparticles are being developed for pure and applied studies. Nanoparticles are simulated by a Poisson-Boltzmann equation (for determining the electric force field in bioelectrolyte media) while an all atom-simulator is used to determine structure. Both modules are optimized for supra-million atom systems. As atomicscale detail is accounted for these modules can determine the influence of cell surface receptors (e.g. binding, destabilization or entry into a membrane) of the nanoparticle.

Microarray data is analyzed by integrating cell modeling and databases with information theory. The result is an automated procedure for discovering the structure of the gene regulatory network and quantifying its physical chemistry. Information theory plays a key role in quantifying uncertainty and using it to guide research on transcription factor/gene interactions. The methodology can be generalized for NMR, mass spec and various microarray technologies.

Cell models and multiplex data analysis software are being used to understand mechanisms of cancer and discover novel diagnostic and treatment strategies. The nanoparticle simulator is being used to understand the behavior of viruses with potential applications to drug and vaccine discovery.


P. Ortoleva Peter J. Ortoleva is a distinguished professor of chemistry at Indiana University. His BS was in physics at RPI and his PhD in applied physics at Cornell. Before joining IU, he was a postdoctoral associate in physical chemistry at MIT. At Indiana University, Professor Ortoleva directs the Center for Cell and Virus Theory (, whose main objective is to develop mathematical and computational models of the physical and chemical processes underlying cell and virus behavior. CCVT researchers are addressing the challenge of understanding the workings of life on multi-, single- and sub-cellular scales. The interdisciplinary approach combines statistical mechanics, quantum chemistry, chemical kinetics, cell physiology, virology, biochemistry, computational sciences, and informatics.

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Researchers should cite this work as follows:

  • Peter J. Ortoleva (2005), "Information Theory and Cell/Nanoparticle Modeling,"

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EE 317, Purdue University, West Lafayette, IN

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