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Peter Kasson

2020

Anna Pabis, Robert J. Rawle, and Peter M. Kasson (2020): Influenza hemagglutinin drives viral entry via two sequential intramembrane mechanisms, Proceedings of the National Academy of Sciences, National Academy of Sciences, Vol 117, Num 13, pp7200-7207

2019

Jennifer M. Hays, David S. Cafiso, and Peter M. Kasson (2019): Hybrid Refinement of Heterogeneous Conformational Ensembles Using Spectroscopic Data, Journal of Physical Chemistry Letters, American Chemical Society, Vol 10, Num 12, pp3410-3414

2017

Peter Kasson (2017): How viral membrane organization controls influenza entry, 2017 Blue Waters Annual Report, pp218-219

2015

Peter Kasson (2015): Simulating Influenza Hemagglutinin Membrane Assemblies, 2015 Blue Waters Annual Report, pp157-158

Great Lakes Consortium awards access to Blue Waters supercomputer to 11 research projects


Jun 2, 2016

How the flu virus enters a cell in the body. Evaluating economic policy impacts of potential future climate change. Understanding the dynamics and physics of atomic matter during galaxy cluster formation. These are just a few of the research projects being pursued by the 11 science and engineering teams from across the country who were awarded time on the Blue Waters supercomputer through the Great Lakes Consortium for Petascale Computation. Over a twelve-month period, these science and engineering teams will have a combined total of more than 4.3 million node hours on Blue Waters.


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U of I, Great Lakes Consortium award Blue Waters resources to 18 research teams


Apr 10, 2014

Eighteen research teams from a wide range of disciplines have been awarded computational and data resources on the sustained-petascale Blue Waters supercomputer at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. Blue Waters is one of the world’s most powerful supercomputers, capable of performing quadrillions of calculations every second and working with quadrillions of bytes of data. Its massive scale and balanced architecture enable scientists and engineers to tackle research challenges that could not be addressed with other computing systems.


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