Explore the words cloud of the ScaleCell project. It provides you a very rough idea of what is the project "ScaleCell" about.
The following table provides information about the project.
Coordinator |
FREIE UNIVERSITAET BERLIN
Organization address contact info |
Coordinator Country | Germany [DE] |
Project website | https://www.mi.fu-berlin.de/en/math/groups/comp-mol-bio/projects/erc_con/index.html |
Total cost | 1˙987˙500 € |
EC max contribution | 1˙987˙500 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2017-COG |
Funding Scheme | ERC-COG |
Starting year | 2018 |
Duration (year-month-day) | from 2018-05-01 to 2023-04-30 |
Take a look of project's partnership.
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1 | FREIE UNIVERSITAET BERLIN | DE (BERLIN) | coordinator | 1˙987˙500.00 |
Biological processes are inherently multi-scalar: exchanging a single amino acid of a protein can affect the macroscopic behavior of a cell. A computational model that can cover these scales and simulate the time evolution of locations, interactions, and atomistic structures of biomolecules in a cell would be transformative for the understanding of biology and the optimization of biotechnological processes. This ERC project will lay the methodological groundwork for such a model. Recent breakthroughs in the long-standing problem of sampling rare transition events in molecular dynamics (MD) simulation have enabled us to simulate biomolecular processes such as folding and binding with atomistic models. The PI has co-pioneered the widely-used Markov State Models (MSMs) that combine extensive distributed MD simulations towards models of the molecular kinetics. Using these methods, we have demonstrated that protein-protein association can be simulated and timescales of seconds can be reached in all-atom models of small protein systems. However, these methods have fundamental limitations to scale to the large biomolecules and the long length-scales involved in cellular signaling. To address these limitations, we will develop the following key technologies and disseminate them in open software:
1. A model that describes protein kinetics as a network of local switches which will overcome scaling limitations of MSMs that suffer from an exponential increase of parameters for large systems. 2. An “effective force field for cells” that predicts structure and kinetics of multi-body protein interactions based on simulations of relatively few protein interactions. 3. A multi-scale method to embed atomistic kinetic models in whole-cell reaction-diffusion simulations.
We will employ these methods and, in collaboration with leading experimentalists, investigate how the mechanochemical protein dynamin couples atomic-detail structure changes to membrane constriction in endocytosis.
year | authors and title | journal | last update |
---|---|---|---|
2018 |
Christoph Fröhner, Frank Noé Reversible Interacting-Particle Reaction Dynamics published pages: 11240-11250, ISSN: 1520-6106, DOI: 10.1021/acs.jpcb.8b06981 |
The Journal of Physical Chemistry B 122/49 | 2020-01-29 |
2019 |
Manuel Dibak, Christoph Fröhner, Frank Noé, Felix Höfling Diffusion-influenced reaction rates in the presence of pair interactions published pages: 164105, ISSN: 0021-9606, DOI: 10.1063/1.5124728 |
The Journal of Chemical Physics 151/16 | 2020-01-29 |
2019 |
Jeffrey K. Noel, Frank Noé, Oliver Daumke, Alexander S. Mikhailov Polymer-like Model to Study the Dynamics of Dynamin Filaments on Deformable Membrane Tubes published pages: 1870-1891, ISSN: 0006-3495, DOI: 10.1016/j.bpj.2019.09.042 |
Biophysical Journal 117/10 | 2020-01-29 |
2019 |
Stefan Klus, Brooke E. Husic, Mattes Mollenhauer, Frank Noé Kernel methods for detecting coherent structures in dynamical data published pages: 123112, ISSN: 1054-1500, DOI: 10.1063/1.5100267 |
Chaos: An Interdisciplinary Journal of Nonlinear Science 29/12 | 2020-01-29 |
2019 |
Frank Noé, Edina Rosta Markov Models of Molecular Kinetics published pages: 190401, ISSN: 0021-9606, DOI: 10.1063/1.5134029 |
The Journal of Chemical Physics 151/19 | 2020-01-29 |
2019 |
Jiang Wang, Simon Olsson, Christoph Wehmeyer, Adrià Pérez, Nicholas E. Charron, Gianni de Fabritiis, Frank Noé, Cecilia Clementi Machine Learning of Coarse-Grained Molecular Dynamics Force Fields published pages: , ISSN: 2374-7943, DOI: 10.1021/acscentsci.8b00913 |
ACS Central Science | 2020-01-29 |
2019 |
Frank Noé, Simon Olsson, Jonas Köhler, Hao Wu Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning published pages: eaaw1147, ISSN: 0036-8075, DOI: 10.1126/science.aaw1147 |
Science 365/6457 | 2020-01-29 |
2019 |
Brooke E. Husic, Frank Noé Deflation reveals dynamical structure in nondominant reaction coordinates published pages: 54103, ISSN: 0021-9606, DOI: 10.1063/1.5099194 |
The Journal of Chemical Physics 151/5 | 2020-01-29 |
2018 |
Hao Wu, Andreas Mardt, Luca Pasquali, Frank Noe Deep Generative Markov State Models published pages: , ISSN: , DOI: |
Proceedings of Neural Information Processing Systems (NeurIPS) 32nd Conference on Neural Infor | 2020-01-29 |
2019 |
Martin K. Scherer, Brooke E. Husic, Moritz Hoffmann, Fabian Paul, Hao Wu, Frank Noé Variational selection of features for molecular kinetics published pages: 194108, ISSN: 0021-9606, DOI: 10.1063/1.5083040 |
The Journal of Chemical Physics 150/19 | 2020-01-29 |
2019 |
Fabian Paul, Hao Wu, Maximilian Vossel, Bert L. de Groot, Frank Noé Identification of kinetic order parameters for non-equilibrium dynamics published pages: 164120, ISSN: 0021-9606, DOI: 10.1063/1.5083627 |
The Journal of Chemical Physics 150/16 | 2020-01-29 |
2018 |
R. Schulz, Y. von Hansen, J. O. Daldrop, J. Kappler, F. Noé, R. R. Netz Collective hydrogen-bond rearrangement dynamics in liquid water published pages: 244504, ISSN: 0021-9606, DOI: 10.1063/1.5054267 |
The Journal of Chemical Physics 149/24 | 2020-01-29 |
2019 |
Moritz Hoffmann, Christoph Fröhner, Frank Noé Reactive SINDy: Discovering governing reactions from concentration data published pages: 25101, ISSN: 0021-9606, DOI: 10.1063/1.5066099 |
The Journal of Chemical Physics 150/2 | 2020-01-29 |
2019 |
Robin Winter, Floriane Montanari, Andreas Steffen, Hans Briem, Frank Noé, Djork-Arné Clevert Efficient multi-objective molecular optimization in a continuous latent space published pages: 8016-8024, ISSN: 2041-6520, DOI: 10.1039/c9sc01928f |
Chemical Science 10/34 | 2020-01-29 |
2019 |
Moritz Hoffmann, Christoph Fröhner, Frank Noé ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics published pages: e1006830, ISSN: 1553-7358, DOI: 10.1371/journal.pcbi.1006830 |
PLOS Computational Biology 15/2 | 2020-01-29 |
2019 |
Simon Olsson, Frank Noé Dynamic graphical models of molecular kinetics published pages: 15001-15006, ISSN: 0027-8424, DOI: 10.1073/pnas.1901692116 |
Proceedings of the National Academy of Sciences 116/30 | 2020-01-29 |
2019 |
Martin Lehmann, Ilya Lukonin, Frank Noé, Jan Schmoranzer, Cecilia Clementi, Dinah Loerke, Volker Haucke Nanoscale coupling of endocytic pit growth and stability published pages: eaax5775, ISSN: 2375-2548, DOI: 10.1126/sciadv.aax5775 |
Science Advances 5/11 | 2020-01-29 |
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The information about "SCALECELL" are provided by the European Opendata Portal: CORDIS opendata.
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