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DigitalLung: Application of High-Performance Computing to Biological System Simulation

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Advances in Computational Biology

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 680))

Abstract

The DigitalLung project represents an attempt to develop a multi-scale capability for simulating human respiration with application to predicting the effects of inhaled particulate matter. To accomplish this objective, DigitalLung integrates macroscale models of integrative human physiology, meso-to-microscale computational fluid dynamics simulations of a breathing human lung, meso-to-nanoscale particle transport and deposition models, and micro-to-nanoscale physical and chemical characterizations of particulate and their mass transfer through the mucosal layer to the epithelium. This chapter describes preliminary results and areas of ongoing research.

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Acknowledgments

This work has been partially funded by NSF (ITR/NGS-0326386, EPS-0556308) and NIH (HL 51971).

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Authors and Affiliations

  1. Department of Aerospace Engineering, Mississippi State University, Starkville, Mississippi State, MS, USA

    David Thompson

Authors
  1. Greg W. Burgreen
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  2. Robert Hester
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  3. Bela Soni
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  4. David Thompson
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  5. D. Keith Walters
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  6. Keisha Walters
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Corresponding author

Correspondence to David Thompson .

Editor information

Editors and Affiliations

  1. Dept. Computer Science, University of Georgia, Athens, 30602-7404, Georgia, USA

    Hamid R. Arabnia

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© 2010 Springer Science+Business Media, LLC

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Burgreen, G.W., Hester, R., Soni, B., Thompson, D., Walters, D.K., Walters, K. (2010). DigitalLung: Application of High-Performance Computing to Biological System Simulation. In: Arabnia, H. (eds) Advances in Computational Biology. Advances in Experimental Medicine and Biology, vol 680. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5913-3_63

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