Bibliography

Articles in International Peer-Reviewed Journal

• 1S. Artemova, S. Grudinin, S. Redon.
  
  A comparison of neighbor search algorithms for large rigid molecules, in: Journal of Computational Chemistry, 2011, vol. 32, n^o 13, p. 2865–2877.
• 2S. Artemova, S. Grudinin, S. Redon.
  
  Fast construction of assembly trees for molecular graphs, in: Journal of Computational Chemistry, 2011, vol. 32, n^o 8, p. 1589-1598.
• 3M. Bosson, S. Grudinin, X. Bouju, S. Redon.
  
  Interactive physically-based structural modeling of hydrocarbon systems, in: Journal of Computational Physics, 2011, vol. 231, n^o 6, p. 2581-2598.
• 4M. Bosson, C. Richard, A. Plet, S. Grudinin, S. Redon.
  
  Interactive quantum chemistry: A divide-and-conquer ASED-MO method, in: Journal of Computational Chemistry, 2012, vol. 33, n^o 7, p. 779-790.
• 5I. Gushchin, V. Gordeliy, S. Grudinin.
  
  Role of the HAMP Domain Region of Sensory Rhodopsin Transducers in Signal Transduction, in: Biochemistry, 2011, vol. 50, p. 574 - 580.
• 6I. Gushchin, A. Reshetnyak, V. Borshchevskiy, A. Ishchenko, E. Round, S. Grudinin, M. Engelhard, G. Büldt, V. Gordeliy.
  
  Active State of Sensory Rhodopsin II: Structural determinants for signal transfer and proton pumping , in: Journal of Molecular Biology, 2011, vol. 412, p. 591 - 600.

International Conferences with Proceedings

• 7A. Bolopion, B. Cagneau, S. Redon, S. Regnier.
  
  Variable gain haptic coupling for molecular simulation, in: World Haptics Conference (WHC), 2011 IEEE, 2011, p. 469–474.

• 8J. Barnes, P. Hut.
  
  A hierarchical 0 (N log iV) force-calculation algorithm, in: Nature, 1986, vol. 324, n^o 4.
• 9C. Bennett.
  
  Mass tensor molecular dynamics, in: J. Comput. Phys., 1975, vol. 19, n^o 3, p. 267–279.
• 10P. Callahan, S. Kosaraju.
  
  A decomposition of multidimensional point sets with applications to k-nearest-neighbors and n-body potential fields, in: Journal of the ACM (JACM), 1995, vol. 42, n^o 1, p. 67–90.
• 11M. Christen, W. van Gunsteren.
  
  Multigraining: an algorithm for simultaneous fine-grained and coarse-grained simulation of molecular systems, in: J. Chem. Phys., 2006, vol. 124, 154106 p.
• 12B. Ensing, S. Nielsen, P. Moore, M. Klein, M. Parrinello.
  
  Energy conservation in adaptive hybrid atomistic/coarse-grain molecular dynamics, in: J. Chem. Theory Comput., 2007, vol. 3, n^o 3, p. 1100–1105.
• 13O. Etzmuss, J. Gross, W. Strasser.
  
  Deriving a particle system from continuum mechanics for the animation of deformable objects, in: Visualization and Computer Graphics, IEEE Transactions on, 2003, vol. 9, n^o 4, p. 538–550.
• 14K. Feenstra, B. Hess, H. Berendsen.
  
  Improving efficiency of large time-scale molecular dynamics simulations of hydrogen-rich systems, in: J. Comput. Chem., 1999, vol. 20, n^o 8, p. 786–798.
• 15L. Greengard, V. Rokhlin.
  
  A fast algorithm for particle simulations, in: J. Comput. Phys., 1987, vol. 73, n^o 2, p. 325–348.
• 16A. Gunaratne.
  
  A penalty function method for constrained molecular dynamics, Citeseer, 2006.
• 17R. Hockney, J. Eastwood.
  
  Computer simulation using particles, Institute of Physics, 1992.
• 18J. Izaguirre, S. Reich, R. Skeel.
  
  Longer time steps for molecular dynamics, in: J. Chem. Phys., 1999, vol. 110, 9853 p.
• 19H. Lin, D. Truhlar.
  
  QM/MM: what have we learned, where are we, and where do we go from here?, in: Theoretical Chemistry Accounts: Theory, Computation, and Modeling (Theoretica Chimica Acta), 2007, vol. 117, n^o 2, p. 185–199.
• 20S. Marrink, H. Risselada, S. Yefimov, D. Tieleman, A. De Vries.
  
  The MARTINI force field: coarse grained model for biomolecular simulations, in: J. Phys. Chem. B, 2007, vol. 111, n^o 27, p. 7812–7824.
• 21J. Monaghan.
  
  Smoothed particle hydrodynamics, in: Reports on Progress in Physics, 2005, vol. 68, 1703 p.
• 22S. Nielsen, R. Bulo, P. Moore, B. Ensing.
  
  Recent progress in adaptive multiscale molecular dynamics simulations of soft matter, in: Phys. Chem. Chem. Phys., 2010, vol. 12, n^o 39, p. 12401–12414.
• 23J. Park, A. Heyden.
  
  Solving the equations of motion for mixed atomistic and coarse-grained systems, in: Mol. Simul., 2009, vol. 35, n^o 10, p. 962–973.
• 24P. Plechac, M. Rousset.
  
  Implicit Mass-matrix Penalization of Hamiltonian Dynamics with Application to Exact Sampling of Stiff Systems, in: Multiscale Modeling & Simulation, 2010, vol. 8, n^o 2, p. 498-539.
• 25M. Praprotnik, L. Site, K. Kremer.
  
  Multiscale simulation of soft matter: From scale bridging to adaptive resolution, in: Annu. Rev. Phys. Chem., 2008, vol. 59, p. 545–571.
• 26M. Preto, S. Tremaine.
  
  A class of symplectic integrators with adaptive time step for separable Hamiltonian systems, in: Astron J, 1999, vol. 118, 2532 p.
• 27F. Rao, M. Spichty.
  
  Thermodynamics and kinetics of large-time-step molecular dynamics., in: J. Comput. Chem., 2011.
• 28S. Reich.
  
  Modified potential energy functions for constrained molecular dynamics, in: Numerical Algorithms, 1998, vol. 19, n^o 1, p. 213–221.
• 29B. Roux.
  
  Implicit solvent models, in: Eastern Hemisphere Distribution, 2001, 133 p.
• 30A. Shih, A. Arkhipov, P. Freddolino, K. Schulten.
  
  Coarse grained protein-lipid model with application to lipoprotein particles, in: J. Phys. Chem. B, 2006, vol. 110, n^o 8, p. 3674–3684.
• 31M. Tuckerman, B. Berne, G. Martyna.
  
  Reversible multiple time scale molecular dynamics, in: J. Chem. Phys., 1992, vol. 97, n^o 3, 1990 p.
• 32A. Voter.
  
  Hyperdynamics: Accelerated molecular dynamics of infrequent events, in: Phys. Rev. Lett., 1997, vol. 78, n^o 20, p. 3908–3911.
• 33G. Voth.
  
  Coarse-graining of condensed phase and biomolecular systems, CRC, 2009.