This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Cell migration is a superb example of biological complexity, as it intertwines biochemical signaling networks with biophysical locomotory processes. While the myriad of molecular components and interactions continue to become identified, the challenge looms to integrate them all into the operation of cell migration as a dynamical system. We are using the Virtual Cell (VC) environment to enable simulations of the locomotory process. The VC is already able to simulate reaction-diffusion equations on the 3-D domains (cellular interior) of complex geometries. Thus, numerical simulation and visualization of a sub-model are being developed that incorporate spatio-temporal dynamics of essential regulatory molecules in the cytoplasm. This includes reaction-diffusion equations describing chemical kinetics, diffusion and transport of actin monomers, actin binding proteins and ions. As the next step, we are enabling VC to solve the reaction-advection-diffusion equations of cytoskeletal mechanics and adhesive system on the 3-D domains and their boundaries, respectively. In addition to incorporating the appropriate numerics infrastructure to deal with the new mathematical formalisms, a key challenge will be to develop graphical representations of the biophysics that can be deployed by the user to fully specify models within a mechanics-enabled problem domain. Such representations would be structured in terms of easily manipulatable sets of components consisting of the structures, molecules, and relevant interactions. Finally, we will expand the VC software in order to dynamically change the cellular geometry to account for the protrusion/retraction movements of the cellular surface. We will adapt finite element techniques to problems of cytoskeletal dynamics with changing geometries.
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| Schaff, James C; Gao, Fei; Li, Ye et al. (2016) Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology. PLoS Comput Biol 12:e1005236 |
| Semenova, Irina; Ikeda, Kazuho; Resaul, Karim et al. (2014) Regulation of microtubule-based transport by MAP4. Mol Biol Cell 25:3119-32 |
| Novak, Igor L; Slepchenko, Boris M (2014) A conservative algorithm for parabolic problems in domains with moving boundaries. J Comput Phys 270:203-213 |
| Michalski, Paul J (2014) First demonstration of bistability in CaMKII, a memory-related kinase. Biophys J 106:1233-5 |
| Azeloglu, Evren U; Hardy, Simon V; Eungdamrong, Narat John et al. (2014) Interconnected network motifs control podocyte morphology and kidney function. Sci Signal 7:ra12 |
| Ditlev, Jonathon A; Mayer, Bruce J; Loew, Leslie M (2013) There is more than one way to model an elephant. Experiment-driven modeling of the actin cytoskeleton. Biophys J 104:520-32 |
| Acker, Corey D; Loew, Leslie M (2013) Characterization of voltage-sensitive dyes in living cells using two-photon excitation. Methods Mol Biol 995:147-60 |
| Loew, Leslie M; Hell, Stefan W (2013) Superresolving dendritic spines. Biophys J 104:741-3 |
| Blasius, T Lynne; Reed, Nathan; Slepchenko, Boris M et al. (2013) Recycling of kinesin-1 motors by diffusion after transport. PLoS One 8:e76081 |
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