Skip to Content

Peter Freddolino

2017

Morteza Khabiri and Peter L. Freddolino (2017): Deficiencies in Molecular Dynamics Simulation-Based Prediction of Protein-DNA Binding Free Energy Landscapes, Journal of Physical Chemistry B, American Chemical Society, Vol 121, Num 20, pp5151-5161

2016

João V. Ribeiro, Rafael C. Bernardi, Till Rudack, John E. Stone, James C. Phillips, Peter L. Freddolino and Klaus Schulten (2016): QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts, Scientific Reports, Springer Nature, Vol 6, Num 1, pp26536

2017

Peter Freddolino (2017): Comprehensive In Silico Mapping of DNA-Binding Protein Affinity Landscapes, 2017 Blue Waters Annual Report, pp212-213

2016

Peter Freddolino (2016): Comprehensive In Silico Mapping of DNA-Binding Protein Affinity Landscapes, 2016 Blue Waters Annual Report, pp208-209

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.


Sources:
 

Great Lakes Consortium awards Blue Waters resources to 9 research teams


Mar 13, 2015

Nine research teams from a wide range of disciplines have been awarded computational and data resources on the 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.


Sources: