2018 SIAM Conference on the Life Sciences

Report by Veronica Ciocanel, Mathematical Biosciences Institute

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The SIAM Conference on the Life Sciences (LS18) was held on August 6-9 in Minneapolis, Minnesota, US, and brought together researchers in mathematics as well as in the life and physical sciences.

The conference kicked off early in the morning on Monday with a great plenary talk by Nathan Kutz from University of Washington. I was very interested in the main theme of this presentation, control in neuroscience systems, where dimensionality reduction is a useful tool in understanding how large networks of neurons interact to produce function. He considered two model systems, the worm C. elegans and the Manduca sexta moth olfactory system. It was fun to see how one could use tools such as dynamic mode decomposition with control to extract low-dimensional models from complex networks of neural activity.

This SIAM meeting was a treat for those of us interested in using dynamical systems and computation to understand intracellular transport mechanisms and organism development. I enjoyed two sessions that started and ended the conference, where the speakers presented new modeling and analysis results for spatiotemporal phenomena in cell and developmental biology. I also organized a session that guided the audience from computational modeling of actin, the smallest filament roads inside the cells (Garegin Papoian, University of Maryland), to dynamical systems models of intermediate filaments (Stephanie Portet, University of Manitoba), and on to SDE frameworks for motor-microtubule interactions (Joe Klobusicky, RPI) and resulting cargo patterns (Heather Brooks, UCLA).

My favorite talk of the whole conference was Peter Kramer’s (RPI) intro to his session on interactions of molecular motors and cytoskeletal structure. In a great introduction to this research field, Dr. Kramer offered an overview on the interesting problems arising at multiple scales: extracting kinetic parameters from experiments of the nanoscale stepping motors; relating the effective dynamics of multiple molecular motors to properties of individual motors at the cargo scale; and interactions of motors and the cytoskeleton at the cellular scale. His session continued with exciting theoretical and computational results on the co-dependence mechanisms of motor interaction, motor diffusion in the cargo membrane, transport in different filament network geometries, and more.

Agent-based models serve as very useful tools to understand collective dynamics of biological and social systems by describing the interactions of individual agents. One session put together by the organizers of the 2018 Mathematical Research Communities (MRC) workshop on agent-based modeling presented new results in swarming and clustering of biological agents, with applications such as chemoreception, zebrafish skin patterns, and locust bands. Several talks, such as the one by Lori Zieglemeier (Macalester College), also presented data-analytic techniques for studying outputs from these dynamical systems. Another session focused on social organization, and the talk by Daniel Balague Guardia (Case Western Reserve University) provided a nice introduction to social force agent-based models for pedestrian crowds with emotion, and well as to kinetic limit PDEs that can be analyzed. Another talk illustrated fun results showing the potential for testing aspects of behavioral contagion in virtual experiments.

For the first time, the SIAM Activity Group on the Life Sciences gave out an Early Career Prize, which was awarded to Sean Lawley from University of Utah, for his significant contributions to the analysis of stochastic phenomena in biology, including work on diffusion processes subject to switching boundaries.

The conference also featured a special session led by Jim Powell, program director for Mathematical Biology at the NSF. This popular session outlined funding opportunities such as DMS Mathematical Biology, the Joint DMS/NIGMS Initiative, Mathematical Biology CAREER awards, as well as special collaboration-based programs such as Collaborative Research in Computational Neuroscience and NSF’s Understanding Rules of Life Big Idea. It was useful to learn about the newly-funded NSF-Simons Mathematical Centers across the US and opportunities to get involved in their upcoming workshops or courses on topics in complex biological systems.

All in all, SIAM LS18 was a fantastic opportunity to learn about new mathematical and computational research applied to a wide variety of biological problems. It was also a chance to meet up with friends from the MRC workshops (2016 math in physiology and 2018 agent-based modeling), as well as to make new connections. Pictures and updates from the conference are available on the SIAM Facebook page and under the #SIAMLS18 hashtag on Twitter.

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