Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
| Created: | 2016-01-25 14:48 |
|---|---|
| Institution: | Isaac Newton Institute for Mathematical Sciences |
| Description: | In the past decades, quantitative biology has been driven by new modelling-based stochastic dynamical systems and partial differential equations. Examples from gene regulation, molecular signalling, cell division and molecular transport, as recently revealed by live cell images, have shown that many processes in cells and in molecular biology are inherently driven by stochastic events. One of the biggest challenges we propose to address in this programme is to develop methods and analysis, as well as efficient algorithms for simulations, to bridge the range of different biological scales. In support of this goal, the programme will focus on
Analysis of stochastic dynamical systems and applications in molecular and cellular biology. Development of efficient computational methods for simulating stochastic equations over various scales. Identifying new research areas. In particular, three interlinked focus areas will run throughout the programme: Analysis, computation and development of non-spatial (well mixed) models. Analysis, computation and development of spatio-temporal reaction-diffusion models, including Brownian dynamics and compartment-based simulations (reaction-diffusion master equation). Multiscale methods. The programme will feature an opening, midterm and closing workshop at the Isaac Newton Institute, as well as a Satellite Meeting. |
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This collection contains 123 media items.
Media items
"No We Can't": Impossibility of efficient leader election by chemical reactions
Doty, D (University of California, Davis)
Tuesday 5th April 2016 - 11:00 to 11:45
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Wed 6 Apr 2016
A constrained approach to the simulation and analysis of stochastic multiscale chemical kinetics
Cotter, S (University of Manchester)
Monday 4th April 2016 - 11:30 to 12:15
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Tue 5 Apr 2016
A stochastic story of two receptors and two ligands
Molina-Paris, C (University of Leeds)
Thursday 7th April 2016 - 14:00 to 14:45
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Tue 12 Apr 2016
Absolute robustness in deterministic and stochastic chemical reaction networks
Enciso, German A. (University of California, Irvine)
Tuesday 10th May 2016 - 15:00 to 16:00
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Wed 1 Jun 2016
Accurate Reaction-Diffusion Operator Splitting on Tetrahedral Meshes for Parallel Stochastic Molecular Simulations
De Schutter, E (Okinawa Institute of Science and Technology)
Wednesday 22nd June 2016 - 11:45 to 12:30
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 4 Jul 2016
Advanced Lecture (U. of Cambridge): Analysis of electrodiffusion in dendritic spines for synaptic transmission
Holcman, D (CNRS - Ecole Normale Superieure Paris)
Friday 24th June 2016 - 11:45 to 12:30
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 4 Jul 2016
An analysis of implicit samplers in the small-noise limit
Lin, K (University of Arizona)
Wednesday 15th June 2016 - 15:00 to 16:00
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 18 Jul 2016
Analysis of Monte Carlo estimators for parametric sensitivities in stochastic chemical kinetics
Rathinam, M (University of Maryland, Baltimore County)
Tuesday 5th April 2016 - 09:45 to 10:30
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Wed 6 Apr 2016
Anomalous Diffusion and Random Encounters in Living Systems
McKinley, S (Tulane University)
Thursday 23rd June 2016 - 11:00 to 11:45
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 4 Jul 2016
Anomalous diffusion in biological membranes and their mathematical description
Metzler, R (Universität Potsdam)
Wednesday 11th May 2016 - 15:00 to 16:00
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Wed 1 Jun 2016
Approximations for Markov chain models
Kurtz, T (University of Wisconsin-Madison)
Monday 4th April 2016 - 09:30 to 10:15
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Tue 5 Apr 2016
Aspects of bacterial persistence
Klumpp, S (Max-Planck-Institut für Kolloid- und Grenzflächenforschung)
Thursday 21st January 2016 - 15:30 to 16:15
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 1 Feb 2016
Bayesan Parameter Estimation and Inference Across Scales
Somersalo, E (Case Western Reserve University)
Monday 4th April 2016 - 14:45 to 15:30
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Tue 5 Apr 2016
Cell biology processes: model building and validation using quantitative data
Baker, R (University of Oxford)
Thursday 23rd June 2016 - 11:45 to 12:30
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 4 Jul 2016
Cellular signalling in T cells is captured by a tractable modular phenotypic model
Dushek, O
Wednesday 6th April 2016 - 09:00 to 09:45
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Fri 8 Apr 2016
Changes in local chromatin structure during homology search: effects of local contacts on search time
Amitai, A (Massachusetts Institute of Technology)
Friday 24th June 2016 - 11:00 to 11:45
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 4 Jul 2016
Closure Scheme for Chemical Master Equations - Is the Gibbs entropy maximum for stochastic reaction networks at steady...
Kaznessis, Y
Friday 8th April 2016 - 09:00 to 09:45
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Tue 12 Apr 2016
Clustering of cell surface receptors: Simulating the mesoscale between reaction-diffusion and atomistic scales
Allard, J (University of California, Irvine)
Thursday 23rd June 2016 - 09:00 to 09:45
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 4 Jul 2016
Computationally efficient simulation of signaling pathways underlying synaptic plasticity
Blackwell, A (George Mason University)
Tuesday 21st June 2016 - 11:45 to 12:30
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Mon 4 Jul 2016
Cox process representation and inference for stochastic reaction-diffusion processes
Schnoerr, D (University of Edinburgh)
Wednesday 8th June 2016 - 15:00 to 16:00
Collection: Stochastic Dynamical Systems in Biology: Numerical Methods and Applications
Institution: Isaac Newton Institute for Mathematical Sciences
Created: Tue 28 Jun 2016