MATHEMATICAL AND COMPUTATIONAL TOOLS (Qing Nie, Theme Leader) The processes and interactions dealt with in Themes A-C are all spatiotemporally dynamic, typically multiscale, and potentially subject to large stochastic effects. Quantitative mathematical and computational analysis of such systems faces substantial challenges, at least using conventional methods. For example, the efficient exploration of large parameter spaces--necessary for model exploration--is hindered by deficiencies in methods for fast, accurate simulation.
In Aim Dia, we propose to develop new fast methods for steady state continuum models that involve multiple spatial scales;
In Aim Dib, we propose a convenient and robust computational framework with a new efficient algorithm for solving systems involving temporally evolving spatial domains - a type of continuum model especially relevant to tissue growth (e.g. in Theme B) Spatiotemporal stochastic effects pose special challenges. While non-spatial stochastic modeling and simulation has provided many recent insights into biochemical reactions, spatial stochastic methods need much further development.
In Aim D2a, we propose a new hybrid spatial model and algorithm that couples continuum stochastic partial differential equations with discrete stochastic reaction-diffusion processes;
In Aim D2b, we propose a multi-scale hybrid model and algorithm that accounts for individual cells, continuum descriptions of morphogens, intracellular regulatory networks, and possible mechanical effects. The tools developed in Aim D2a can be applied to the hybrid approach in Aim D2b. These modeling frameworks will help projects in Themes A-C explore stochastic effects more freely and efficiently than is currently possible. A common goal in Systems Biology is to use large biological data sets to "learn" the topology and parameters of biological networks. Defining complex gene regulatory networks is particularly important for understanding systems that drive spatial phenomena, such as patterning and morphogenesis. Yet, currently, most network inference is done using perturbation-series, or time-series data, but not continuous spatial information. We propose to begin to address this deficiency by starting to develop, in Aim D3, methods for inferring spatiotemporal models from spatiotemporal data. This approach begins with the development of a regularization framework to enable incorporation of different kinds of data into inference algorithms, and continues with development of approaches to use imaging data in network inference. One of our major goals in the development of computational tools is robustness. To meet the need for large scale model exploration that the kinds of biology in this proposal require, we must create methods that workwell over large ranges of parameter space, initial and/or boundary conditions, and model architecture. Although we can always expect trade-offs between computafional robustness and speed, computational frameworks that require minimal fine-tuning to the specifics of individual models are likely to be much more useful to the work in this proposal, and to the Systems Biology community in general.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Specialized Center (P50)
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Special Emphasis Panel (ZGM1-CBCB-3)
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University of California Irvine
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Kang, Dong-Ku; Ali, M Monsur; Zhang, Kaixiang et al. (2014) Rapid detection of single bacteria in unprocessed blood using Integrated Comprehensive Droplet Digital Detection. Nat Commun 5:5427
Seiler, Magdalene J; Aramant, Robert B; Jones, Melissa K et al. (2014) A new immunodeficient pigmented retinal degenerate rat strain to study transplantation of human cells without immunosuppression. Graefes Arch Clin Exp Ophthalmol 252:1079-92
Pate, Kira T; Stringari, Chiara; Sprowl-Tanio, Stephanie et al. (2014) Wnt signaling directs a metabolic program of glycolysis and angiogenesis in colon cancer. EMBO J 33:1454-73
Annibale, Paolo; Gratton, Enrico (2014) Advanced fluorescence microscopy methods for the real-time study of transcription and chromatin dynamics. Transcription 5:
Paladino, Simona; Lebreton, St├ęphanie; Tivodar, Simona et al. (2014) Golgi sorting regulates organization and activity of GPI proteins at apical membranes. Nat Chem Biol 10:350-7
Lei, Jinzhi; Levin, Simon A; Nie, Qing (2014) Mathematical model of adult stem cell regeneration with cross-talk between genetic and epigenetic regulation. Proc Natl Acad Sci U S A 111:E880-7
Conesa, Ana; Mortazavi, Ali (2014) The common ground of genomics and systems biology. BMC Syst Biol 8 Suppl 2:S1
Bonaventura, Gabriele; Barcellona, Maria Luisa; Golfetto, Ottavia et al. (2014) Laurdan monitors different lipids content in eukaryotic membrane during embryonic neural development. Cell Biochem Biophys 70:785-94
Holmes, William R (2014) An efficient, nonlinear stability analysis for detecting pattern formation in reaction diffusion systems. Bull Math Biol 76:157-83
Aland, Sebastian; Egerer, Sabine; Lowengrub, John et al. (2014) Diffuse interface models of locally inextensible vesicles in a viscous fluid. J Comput Phys 277:32-47

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