Computational models for developmental and cell biology: A celebration of the works of Prof. Ching-Shan Chou

Arthur D. Lander

University of California Irvine, Irvine, CA (Center for Complex Biological Systems, and Department of Developmental and Cell Biology)

"Control and Stability in Proliferative Dynamics"

The control of cell proliferation—the central process in creating, maintaining, and regenerating tissues of defined sizes and shapes—is a tricky business, because proliferation is fundamentally autocatalytic, and therefore prone to instability. Yet multicellular organisms achieve great feats of speed, precision, and stability in the production and maintenance of tissues. Moreover, they do so in the face of considerable stochasticity in the outcomes of cell divisions. Experimental studies have identified generic strategies—all based on some form of collective integral feedback—that can be shown, mathematically, to achieve many of these control objectives. However, the reliance of such strategies on cell-cell interaction creates fragilities, arising from limits on the distances over which intercellular signals spread; limits on the time scales over which perturbations can be managed; and situational ultrasensitivity to stochastic fluctuations. I will discuss the tradeoffs these fragilities impose, and how they influence what control organisms can achieve safely. I will raise the possibility that such fragilities create opportunities for rare, stochastic progression to states of uncontrolled growth, i.e., cancer, and suggest that such transitions provide a better model for cancer initiation than current models based on genetic determinism.

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Dongbin Xiu

Ohio State University (Department of Mathematics)

"Data driven modeling of partially observed biological systems"

We present a framework of flow map learning (FML) for predictive modeling of unknown dynamical systems from measurement data, with applications to biological systems. The method is designed to discover the flow map operator behind the data and utilize deep neural network (DNN) as the main numerical technique for the discovery. Once an accurate DNN model for the flow map is constructed, it serves as a predictive model for the unknown system and enables us to conduct long-term system prediction and analysis. The FML framework is highly versatile, as it allows one to construct accurate models when only a limited subset of the system parameters and state variables are observed.

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Tau-Mu Yi

University of California, Santa Barbara (Molecular, Cellular, and Developmental Biology)

"Systems Biology of Cell Polarity in Yeast"

Gradient sensing and response is a basic cellular behavior. Cells sense a chemical gradient and then respond by moving or projecting up the gradient. During this process of breaking symmetry, protein components localize to the front (or back) of the cell resulting in cell polarity. In this work, we characterized an information measure for cell polarity that applies to non-motile cells responding to a chemical gradient. The central idea is that polarization represents information about the direction of the gradient. Building upon previous work in the literature, we applied a theory of optimal gradient sensing and response in the presence of external noise based on the information capacity of a Gaussian channel. We compared the theory to experimental data on yeast mating projection growth in a pheromone gradient and demonstrated that slow ligand binding to receptor is the limiting factor in yeast gradient sensing. Finally, we showed that temporal averaging can help overcome the slow binding rate to achieve greater accuracy but resulting in a slow mating response.
Additional authors: Ching-Shan Chou

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Avner Friedman

Ohio State University (Department of Mathematics)

"How breast cancer metastasize into the bone"

Bone marrow is a “fertile soil” for growth and proliferation of cancer cells. But in order to metastasize into the bone, breast cancer cells first need to degrade and weaken the hard layer at the bone surface. To facilitate this process they secret, sometime in advance, organelles (called exosomes) that contain DNA, mRNA , microRNA and proteins. It is now known that some of the microRNAs destroy the balance between bone formation and bone resorption, which results in bone lesions, and allow cancer cells to penetrate into the bone interior. In this talk I shall describe this process by a mathematical model, and introduce drugs that can increase bone density to the normal level and thus may protect the bone from invasion by cancer cells. This work is jointly with Nourridine Siewe.

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Chiu-Yen Kao

Claremont McKenna College (Mathematical Sciences)

"Our math and biology journey: A tribute to Ching-Shan Chou"

In this talk, I will bring you to a time machine ride to get to know Professor Ching-Shan Chou’s background, interests that we shared, and work that we had done together. In particular, highlight book projects, common interests, research works on propagation of cutaneous thermal injury, vibration of rods and plates, and fast sweeping methods for steady state problems for hyperbolic conservation laws.

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