Mathematical Biology Seminar - Spring 2023

February 8

Albane Thiery, University of Pennsylvania

Host: Enkeleida Lushi

Microswimmers Navigating Complex Fluids

Microorganisms have evolved to thrive in fluids that exhibit non-Newtonian behaviors. However, the intricacy of the relevant non-linear fluid responses has hindered our understanding of the interaction between complex environments and swimming. Here, we propose a model for two experimental systems that show improved swimmer performance in a complex medium: helical swimming in a suspension and rheotaxis in a shear-thinning fluid. In both cases, a mix of theoretical arguments and simulations explains the enhancement in swimming efficiency.

February 22

Yariv Aizenbud, Yale University

Host: Kristina Wicke

Recovering Tree Models via Spectral Graph Theory

Modelling data by latent tree models is a powerful approach in multiple applications. A canonical example of this setting is the "tree of life", where the evolutionary history of a set of organisms is inferred by their DNA. Generally, in latent tree models, the main task is to infer the structure of the tree, given only observations of its terminal nodes. While inferring a tree structure is a common task, in many applications, a robust algorithm for the recovery of large trees is still missing.

In this talk, we will see a new method for the recovery of latent tree models, which is based on spectral graph theory. We show that the hidden tree structure is strongly related to the spectral properties of a graph, defined over the terminal nodes of the tree. Finally, we see that while in terms of accuracy the method performs similarly to state-of-the-art methods, it is significantly more computationally efficient.  

March 8

Nessy Tania, Senior Principal Scientist, Quantitative Systems Pharmacology, Pfizer Worldwide Research, Development, and Medical

Host: Casey Diekman

Shaping Your Own Career as a Mathematical Biologist

In this talk, I will share some of my personal journey as a math biologist and applied mathematician who had pursued a tenure-track position in academia and is now working as a research scientist in the biopharma industry. I will discuss similarities and differences, rewards and challenges that I have encountered in both positions. On a more practical aspect, I will discuss how current trainees can prepare for a career in industry (specifically biopharma) and how to seek those opportunities. I will also describe the emerging field of Quantitative Systems Pharmacology (QSP): its deep root in mathematical biology and how it is currently shaping the drug development process. Finally, I will share some of my own ongoing work as a QSP modeler who is supporting the Rare Disease Research Unit at Pfizer. As a key takeaway, I hope to share that there are multiple paths to success and a rewarding and stimulating career in applied mathematics.

April 12

Zhangli Peng, University of Illinois in Chicago

Host: Yuan-nan Young

Multiscale Modeling of Structures of the Cell and Beyond

While a cell is like a factory of chemical reactions, its structural components are crucial for its normal functions and survival. Molecular mutations of structural components can lead to altered mechanical properties and malfunction of the cell. Unlike hard materials used for buildings and cars, most structural components of the cell are soft and more complex. It is a grand computational challenge to predict the mechanical behaviors of the cell due to its sophisticated mesoscopic structures, dynamic self-assembly, and strong entropic contributions to the free energy. In this seminar, I will show examples of applying the microstructure-based multiscale modeling technique to investigate structures of the cell. I will demonstrate how mutations of structural and membrane proteins impact the process of red blood cells passing through the slits in the spleen and in the corresponding bio-mimicking microfluidic devices. I will also show how the anisotropic properties of microtubules affect the behavior of primary cilia under thermal fluctuations and shear flow. These computational predictions are not only important for understanding physiological functions but also critical for uncovering the mechanisms of genetic diseases, such as congenital hemolytic anemia and polycystic kidney disease. In addition, I will also show several examples of applying multiscale modeling to microfluidic/nanofluidic systems, such as inertial microfluidics, acoustic microfluidics, and nanopores.

Biography:
Zhangli Peng is an Assistant Professor in the Department of Biomedical Engineering in the University of Illinois Chicago. He got his Ph.D. from the University of California San Diego and carried out his postdoctoral research in the Massachusetts Institute of Technology. His research area is computational science and engineering. Specifically, his research directions include: 1) Multiscale modeling, such as coupling of continuum-based macroscale modeling with particle-based mesoscale/microscale simulations; 2) Biomechanics and biophysics of cells/organelles/molecules/tissues, such as red blood cells, primary cilia, nuclei, cytoskeletal proteins, DNA/RNA, and blood vessel walls; 3) Modeling of microfluidics/nanofluidics, such as acoustic microfluidics, inertial microfluidics, and nanopores. He has co-authored over 41 peer-reviewed journal articles and is a co-inventor on two patents.

April 18

Tomer Weiss, Informatics, NJIT

Host: Enkeleida Lushi

Simulating Multi-Agent Dynamics for Physical and Virtual Worlds

Collective behavior is all around us, from the motion of pedestrian crowds, to animals such as birds and insect swarms.  Understanding the mechanics of such behaviors has wide range implications in traffic mitigation, robotics, virtual worlds, and emergency preparation. In this talk, I will present our approach for mathematical modeling, online learning, and simulation of multi-agent dynamics.

First, I will demonstrate a physics-inspired constraint-based approach for multi-agent simulation, which is an alternative to traditional velocity-obstacle approaches in robotics. Our method simulates dense crowds in interactive rates for hundreds of thousands of agents, which was previously unachievable. This work received the best paper award in the ACM SIGGRAPH conference on Motion in Games 2017.

Second, I will discuss our recent results in Deep Reinforcement Learning for multi-agent navigation, which allows fine-grain rewards-based strategies for controlling agent locomotion behaviors. We will illustrate how our techniques can be applied to robot navigation in pedestrian crowds.

May 3

Ruby Kim, Department of Mathematics at the University of Michigan

Host: Casey Diekman

Mathematical Modeling of the Molecular Clock and the Dopaminergic System

Circadian rhythms are ~24-hour biological rhythms that influence our physiology, including the daily concentrations of dopamine, an important neurotransmitter. At the molecular level, circadian rhythms are generated by a transcription-translation feedback loop often studied as a limit cycle oscillator. This talk will be about some mathematical modeling of the interactions between the molecular clock and the dopaminergic system. Our results corroborate the hypothesis that specific clock proteins activate or inhibit the expression of two dopaminergic enzymes. We will also discuss the influence of light signaling on the molecular clock and how dopamine speeds up the entrainment of the molecular clock to the light-dark cycle.