Jay Newby

Assistant Professor

Mathematical and Statistical Sciences

University of Alberta

Research

My research is primarily focused on developing mechanistic stochastic models of molecular motion, biomechanics, and chemistry in micron-scale environments such as cells and extracellular polymer matrices. Cells function through a highly complex set of interconnected chemical and mechanical processes, and on the micron scale, thermal fluctuations cause random molecular motion and impose random mechanical fluctuations on biopolymers. Hence, cellular processes are intrinsically complex, nonlinear, and stochastic. Mechanistic stochastic models are quickly becoming essential for understanding the micron-scale machinery of living organisms. One example from my work is the kinetic coupling between stochastic molecular motors and microtubules to boost and guide otherwise slow and random diffusive transport of cargo across the cell. Similar kinetic and diffusive processes are at play in extracellular mechanisms, e.g., antibody-based viral immunity.

Selected Publications

J Newby, A Schaefer, P Lee, MG Forest, and S Lai. Convolutional neural networks automate detection for tracking of submicron-scale particles in 2D and 3D. PNAS, 2018.

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J Newby, L Schiller, T Wessler, J Edelstein, MG Forest, and S Lai. A blueprint for robust crosslinking of mobile species in biogels with weakly adhesive molecular anchors. Nature Communications, 2017.

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J Newby and J Allard. First-passage time to clear the way for receptor-ligand binding in a crowded environment. Phys. Rev. Lett., 2016.

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J Newby and M Schwemmer. Effects of moderate noise on a limit cycle oscillator: Counterrotation and bistability. Phys. Rev. Lett., 2014.

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J Newby, P Bressloff, and J Keener. The role of stochastic potassium channels in spontaneous action potential initiation. Phys. Rev. Lett., 2013.

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