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Vijay S. Pande

Affiliations: 
Stanford University, Palo Alto, CA 
Area:
theoretical methods to understand the physical properties of biological molecules
Website:
https://profiles.stanford.edu/vijay-pande
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"Vijay Pande"
Bio:

http://pande.stanford.edu/people/vijay-pande/
Pande, Vijay Satyanand Freezing transition of heteropolymers Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1995.

Mean distance: 9.21
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Parents

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Philip Warren Anderson research assistant 1988-1992 Princeton (Physics Tree)
 (B.A.)
Alexander Yu. Grosberg grad student 1995 MIT
Toyoichi Tanaka grad student 1995 MIT

Children

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Brooke Husic grad student
Carlos Xavier Hernández grad student 2013- Stanford
Stefan M. Larson grad student 2004 Stanford
Bojan Zagrovic grad student 2004 Stanford
Sidney P. Elmer grad student 2005 Stanford
Young M. Rhee grad student 2005 Stanford
Michael R. Shirts grad student 2005 Stanford
Mark A. Engelhardt grad student 2006 Stanford
Christopher D. Snow grad student 2006 Stanford
Nina S. Hinrichs grad student 2007 Stanford
Guha Jayachandran grad student 2007 Stanford
Eric J. Sorin grad student 2007 Stanford
V. Vishal grad student 2007 Stanford
Jeremy L. England grad student 2009 Stanford
Paula M. Petrone grad student 2009 Stanford
Gregory R. Bowman grad student 2006-2010 Stanford
Vincent A. Voelz grad student 2007-2011 Stanford
Peter M. Kasson post-doc Stanford
Lillian T. Chong post-doc 2002-2006 Stanford
Xuhui Huang post-doc 2006-2008 Stanford
John D. Chodera post-doc 2007-2008 Stanford
Kai J Kohlhoff post-doc 2009-2010 Stanford Medical School (Computational Biology Tree)
Lutz G. Maibaum post-doc 2009-2011 Stanford
Diwakar Shukla post-doc 2011-2014
Lee-Ping Wang post-doc 2011-2015 Stanford

Collaborators

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William C. Swope collaborator
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Publications

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Eastman P, Galvelis R, Peláez RP, et al. (2023) OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The Journal of Physical Chemistry. B
Eastman P, Galvelis R, Peláez RP, et al. (2023) OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. Arxiv
Voelz VA, Pande VS, Bowman GR. (2023) Folding@home: achievements from over twenty years of citizen science herald the exascale era. Arxiv
Voelz VA, Pande VS, Bowman GR. (2023) Folding@home: Achievements from over 20 years of citizen science herald the exascale era. Biophysical Journal
McKiernan KA, Koster AK, Maduke M, et al. (2020) Dynamical model of the CLC-2 ion channel reveals conformational changes associated with selectivity-filter gating. Plos Computational Biology. 16: e1007530
Dalton K, Lopez T, Pande V, et al. (2020) REP-X: An Evolution-guided Strategy for the Rational Design of Cysteine-less Protein Variants. Scientific Reports. 10: 2193
Kostrz DN, Wayment-Steele HK, Wang J, et al. (2020) A Modular DNA Scaffold to Study Protein-Protein Interactions at Single-Molecule Resolution Biophysical Journal. 118: 187a
Kostrz D, Wayment-Steele HK, Wang JL, et al. (2019) A modular DNA scaffold to study protein-protein interactions at single-molecule resolution. Nature Nanotechnology
Feinberg EN, Sur D, Wu Z, et al. (2018) PotentialNet for Molecular Property Prediction. Acs Central Science. 4: 1520-1530
Wayment-Steele HK, Pande VS. (2018) Note: Variational encoding of protein dynamics benefits from maximizing latent autocorrelation. The Journal of Chemical Physics. 149: 216101
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