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NANO-D - 2015
NANO-D - 2015
Project-Team Nano-d
Members
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
Dissemination
Bibliography
Project-Team Nano-d
Members
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
Dissemination
Bibliography


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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 2P. Buslaev, V. I. Gordeliy, S. Grudinin, I. Y. Gushchin.

    Principal component analysis of lipid molecule conformational changes in molecular dynamics simulations, in: Journal of Chemical Theory and Computation, January 2016. [ DOI : 10.1021/acs.jctc.5b01106 ]

    https://hal.inria.fr/hal-01258167
  • 3L. Debreu, E. Neveu, E. Simon, F.-X. Le Dimet, A. Vidard.

    Multigrid solvers and multigrid preconditioners for the solution of variational data assimilation problems, in: Quarterly Journal of the Royal Meteorological Society, September 2015. [ DOI : 10.1002/qj.2676 ]

    https://hal.inria.fr/hal-01246349
  • 4S. Grudinin, P. Popov, E. Neveu, G. Cheremovskiy.

    Predicting Binding Poses and Affinities in the CSAR 2013―2014 Docking Exercises Using the Knowledge-Based Convex-PL Potential, in: Journal of Chemical Information and Modeling, 2015. [ DOI : 10.1021/acs.jcim.5b00339 ]

    https://hal.inria.fr/hal-01258022
  • 5P. Popov, S. Grudinin.

    Knowledge of Native Protein–Protein Interfaces Is Sufficient To Construct Predictive Models for the Selection of Binding Candidates, in: Journal of Chemical Information and Modeling, September 2015, vol. 55, no 10, pp. 2242–2255. [ DOI : 10.1021/acs.jcim.5b00372 ]

    https://hal.inria.fr/hal-01229886
  • 6D. W. Ritchie, S. Grudinin.

    Spherical polar Fourier assembly of protein complexes with arbitrary point group symmetry, in: Journal of Applied Crystallography, February 2016, vol. 49, no 1, pp. 158-167. [ DOI : 10.1107/S1600576715022931 ]

    https://hal.inria.fr/hal-01261402

Other Publications

References in notes
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  • 22E. Cances, F. Castella, P. Chartier, E. Faou, C. L. Bris, F. Legoll, G. Turinici.

    Long-time averaging for integrable Hamiltonian dynamics, in: Numerische Mathematik, 2005, vol. 100, pp. 211-232, 10.1007/s00211-005-0599-0.

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  • 23Q. Chaudhry, M. Scotter, J. Blackburn, B. Ross, A. Boxall, L. Castle, R. Aitken, R. Watkins.

    Applications and implications of nanotechnologies for the food sector, in: Food Additives & Contaminants: Part A, 2008, vol. 25, no 3, pp. 241-258.

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  • 24X. Chen, S. S. Mao.

    Titanium Dioxide Nanomaterials: Synthesis, Properties, Modifications, and Applications, in: ChemInform, 2007, vol. 38, no 41.

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    DARS (Decoys As the Reference State) potentials for protein-protein docking, in: Biophysical journal, 2008, vol. 95, no 9, pp. 4217–4227.
  • 26S. R. Comeau, C. J. Camacho.

    Predicting oligomeric assemblies: N-mers a primer, in: Journal of structural biology, 2005, vol. 150, no 3, pp. 233–244.
  • 27S. Cooper, F. Khatib, A. Treuille, J. Barbero, J. Lee, M. Beenen, A. Leaver-Fay, D. Baker, Z. Popovic, F. Players.

    Predicting protein structures with a multiplayer online game, in: Nature, 2010, vol. 466, pp. 756-760.
  • 28M. Curreli, A. H. Nadershahi, G. Shahi.

    Emergence of nanomedical devices for the diagnosis and treatment of cancer: the journey from basic science to commercialization, in: International Journal of Technology Transfer and Commercialisation, 2008, vol. 7, no 4, pp. 290-307.
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    The Fast Multipole Method: Numerical Implementation, in: Journal of Computational Physics, 2000.
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  • 32H. Dietz, S. M. Douglas, W. M. Shih.

    Folding DNA into Twisted and Curved Nanoscale Shapes, in: Science, 2009, vol. 325, no 5941, pp. 725-730. [ DOI : 10.1126/science.1174251 ]

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  • 33S. J. Fleishman, T. A. Whitehead, D. C. Ekiert, C. Dreyfus, J. E. Corn, E.-M. Strauch, I. A. Wilson, D. Baker.

    Computational Design of Proteins Targeting the Conserved Stem Region of Influenza Hemagglutinin, in: Science, 2011, vol. 332, no 6031, pp. 816-821. [ DOI : 10.1126/science.1202617 ]

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    Structure, properties and wear performance of nano-multilayered TiAlCrSiYN/TiAlCrN coatings during machining of Ni-based aerospace superalloys, in: Surface and Coatings Technology, 2010, vol. 204, pp. 3698 - 3706. [ DOI : 10.1016/j.surfcoat.2010.04.050 ]

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    Structure and Dynamics of Nanocatalysts, in: Microscopy and Microanalysis, 2010, vol. 16, no Supplement S2, pp. 1712-1713.

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  • 39A. Heyden, D. G. Truhlar.

    Conservative Algorithm for an Adaptive Change of Resolution in Mixed Atomistic/Coarse-Grained Multiscale Simulations, in: Journal of Chemical Theory and Computation, 2008, vol. 4, no 2, pp. 217-221.

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    Comparison of multiple Amber force fields and development of improved protein backbone parameters, in: Proteins: Structure, Function, and Bioinformatics, 2006, vol. 65, no 3, pp. 712–725.

    http://dx.doi.org/10.1002/prot.21123
  • 42H. Hwang, T. Vreven, J. Janin, Z. Weng.

    Protein–protein docking benchmark version 4.0, in: Proteins: Structure, Function, and Bioinformatics, 2010, vol. 78, no 15, pp. 3111–3114.
  • 43J. Janin, K. Henrick, J. Moult, L. T. Eyck, M. J. Sternberg, S. Vajda, I. Vakser, S. J. Wodak.

    CAPRI: a critical assessment of predicted interactions, in: Proteins: Structure, Function, and Bioinformatics, 2003, vol. 52, no 1, pp. 2–9.
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  • 48D. Kozakov, R. Brenke, S. R. Comeau, S. Vajda.

    PIPER: an FFT-based protein docking program with pairwise potentials, in: Proteins: Structure, Function, and Bioinformatics, 2006, vol. 65, no 2, pp. 392–406.
  • 49D. Kozakov, K. H. Clodfelter, S. Vajda, C. J. Camacho.

    Optimal clustering for detecting near-native conformations in protein docking, in: Biophysical journal, 2005, vol. 89, no 2, pp. 867–875.
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    Indicating the development stage of nanotechnology in the textile and clothing industry, in: International Journal of Nanotechnology, 2007, vol. 4, no 6, pp. 667-679.
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    Nanoelectronics from the bottom up, in: Nature materials, 2007, vol. 6, no 11, pp. 841-850.
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    Energy minimization in low-frequency normal modes to efficiently allow for global flexibility during systematic protein–protein docking, in: Proteins: Structure, Function, and Bioinformatics, 2008, vol. 70, no 3, pp. 794–809.
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    SwarmDock and the use of normal modes in protein-protein docking, in: International journal of molecular sciences, 2010, vol. 11, no 10, pp. 3623–3648.
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    Adaptive Multiscale Molecular Dynamics of Macromolecular Fluids, in: Phys. Rev. Lett., Dec 2010, vol. 105, 237802.

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  • 56A. Nikitin, X. Li, Z. Zhang, H. Ogasawara, H. Dai, A. Nilsson.

    Hydrogen Storage in Carbon Nanotubes through the Formation of Stable C-H Bonds, in: Nano Letters, 2008, vol. 8, no 1, pp. 162-167, PMID: 18088150.

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  • 57P. Popov, S. Grudinin.

    Rapid determination of RMSDs corresponding to macromolecular rigid body motions, in: Journal of computational chemistry, 2014, vol. 35, no 12, pp. 950–956.
  • 58P. Popov, S. Grudinin.

    Knowledge of Native Protein–Protein Interfaces Is Sufficient To Construct Predictive Models for the Selection of Binding Candidates, in: Journal of chemical information and modeling, 2015, vol. 55, no 10, pp. 2242–2255.
  • 59P. Popov, D. W. Ritchie, S. Grudinin.

    DockTrina: Docking triangular protein trimers, in: Proteins: Structure, Function, and Bioinformatics, 2014, vol. 82, no 1, pp. 34–44.
  • 60M. Praprotnik, L. Delle Site, K. Kremer.

    Adaptive resolution scheme for efficient hybrid atomistic-mesoscale molecular dynamics simulations of dense liquids, in: Phys. Rev. E, Jun 2006, vol. 73, 066701.

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  • 61M. Praprotnik, S. Matysiak, L. D. Site, K. Kremer, C. Clementi.

    Adaptive resolution simulation of liquid water, in: Journal of Physics: Condensed Matter, 2007, vol. 19, no 29, 292201.

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    A macromolecule in a solvent: Adaptive resolution molecular dynamics simulation, in: The Journal of Chemical Physics, 2007, vol. 126, no 13, 134902. [ DOI : 10.1063/1.2714540 ]

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  • 63M. Praprotnik, L. D. Site, K. Kremer.

    Multiscale Simulation of Soft Matter: From Scale Bridging to Adaptive Resolution, in: Annual Review of Physical Chemistry, 2008, vol. 59, no 1, pp. 545-571.

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