Archives: Fall 2022, Spring 2022, Winter 2022, Spring 2021, Fall 2021

Links :  UCR Interdisciplinary Center for Quantitative Modeling in Biology

     UCR Math Department seminar

               PDE and Applied Math Seminar

Please contact mykhailp@ucr.edu if you are interested in attending this seminar.

Both virtual and in-person talks will provide hybrid options for seminar participants. One might join the seminars in the designated room or online through Zoom.

Winter 2023 

Jan 9, 4:00 PM (Mon)   Dr. Zahra Aminzare, University of Iowa, (jointly with Mathematics Department Colloquium - [event link])

Jan 10, 2:00 PM (Tue)  Organization meeting 

Jan 17, 4:00 PM (Tue)  Dr. Peijie Zhou, UC Irvine, (jointly with Mathematics Department Colloquium - [event link])

Jan 24, 4:00 PM (Tue)  Dr. Gregory Handy, University of Chicago, (jointly with Mathematics Department Colloquium - [event link])

Jan 26, 4:00 PM (Thu)  Dr. Shuang Liu, University of California, San Diego, (jointly with Mathematics Department Colloquium - [event link])

Jan 27, 4:00 PM (Fri)    Dr. Kelsey Gasior, University of Ottawa, Canada, (jointly with Mathematics Department Colloquium - [event link])

Feb 7, 2:00 PM (Tue)  Dr. Wayne Hayes, UC Irvine

Feb 14, 2:00 PM (Tue)  Dr. Mykhailo Potomkin, UC Riverside

Feb 21, 2:00 PM (Tue) Dr. Eric Mjolsness, UC Irvine

Feb 28, 2:00 PM (Tue) Dr. Vikram Adhikarla, City of Hope Comprehensive Cancer Center 

Mar 7, 2:00 PM (Tue) Dr. Alexander P. Hoover, Cleveland State University

Mar 14, 2:00 PM (Tue) Dr. Brato Chakrabarti, Flatiron Institute 

All talks:

Mar. 14, 2023, 2:00-2:50 PM Pacific Time

Dr. Brato Chakrabarti, Flatiron Institute

Title: The waves within us: hydrodynamics of passive and active filaments

Abstract: An important class of microscale fluid-structure interactions in physics and biology involves the interactions and deformations of flexible elastica, both passive and active, with ambient fluid flows. Examples include the swimming of microorganisms using internally actuated cilia or flagella and the transport of material by the coordinated action of ciliary carpets. I will discuss two problems concerning the dynamics of passive and active fibers in flows. First, I will talk about the novel buckling instabilities and complex shapes of single actin polymers in simple flows and their importance in the rheology of complex fluids. I will then discuss a biophysical model of a spontaneously beating cilium that incorporates various details of their microscopic physics. Using this model, I will illustrate how beds of beating cilia self-organize to form large-scale metachronal waves that help in fluid transport. This work has implications for understanding fundamental biological problems, such as vertebrate symmetry-breaking.

Bio: Dr. Brato Chakrabarti is a Research Fellow in the Center for Computational Biology (CCB) at Flatiron Institute, New York. Before joining Flatiron, he obtained his Ph.D. from the Department of Mechanical and Aerospace Engineering at UC San Diego, advised by Professor David Saintillan. Dr. Brato Chakrabarti primarily works on developing theoretical and computational tools to study fluid-structure interactions in Stokes flow relevant for various biophysical problems.

Mar. 7, 2023, 2:00-2:50 PM Pacific Time

Dr. Alexander Hoover, Cleveland State University

Title: Neuromechanical Wave Resonance in Fluid Pumping 

Abstract: Many biomechanical systems are activated by a nervous system that initiates and coordinates muscular contraction. In these systems, there are a number of intrinsic time scales, such as the speed and firing frequency of an action potential or the natural vibrational frequency of an elastic appendage or body, that influence the performance of these systems. In this talk, we explore the dynamics that neuromuscular activation has in fluid pumping systems and use numerical simulations to describe the interplay between active muscle contraction, passive body elasticity, and fluid forces. This model is then used to explore the interplay between the speed of neuromechanical activation, fluid dynamics, and the material properties of systems. The investigation of the interplay of these timescales then leads to discovery a phenomenon known as neuromechanical wave resonance. This phenomenon is an important design principle for the actuation of tissue-engineered pumps and soft-bodied robotics.

Bio: Prof. Alexander Hoover is an assistant professor in the Department of Mathematics and Statistics at Cleveland State University. He received his PhD from the University of North Carolina at Chapel Hill and was a postdoctoral fellow at Tulane University in New Orleans. His research area is broadly in applied and computational mathematics, with a focus on mathematical biology, computational fluid dynamics, and biomechanics. Much of his work involves developing fluid-structure interaction models of organismal systems, using in-silico HPC models to understand the fundamental physics driving these biomechanical systems.

Feb. 28, 2023, 2:00-2:50 PM Pacific Time

Dr. Vikram Adhikarla, City of Hope Comprehensive Cancer Center

Title: Mathematical modeling in targeted radionuclide therapies 

Abstract: Targeted radionuclide therapies (TRT) involve the delivery of a radiotherapeutic to cancer cells with the goal of specifically targeting the tumor cells with radiation. In contrast to external beam radiotherapy, the agent delivering the radiation in case of TRT is present within the body. Mathematical models proposed in the field of radiotherapy have long been used to deliver external beam radiation therapies. Such models are also uniquely positioned to predict dose response of cancer cells to TRT. A successful modeling framework enables optimization of dosing and scheduling regimens of TRT, both as a monotherapy as well as a combination therapy with other therapies such as immunotherapy. Here we develop a mathematical modeling framework for TRT and extend the framework by incorporating a vasculature component in it. Along with an introduction to targeted imaging and therapy, the talk will give the audience a flavor of how mechanistic mathematical models are utilized in biological systems.

Bio: Dr. Vikram Adhikarla is an Assistant Research Professor in the Department of Computational and Quantitative Medicine at City of Hope in Duarte. He obtained his Ph.D. in Physics in 2014 from the University of Wisconsin-Madison with thesis focusing on mathematical modeling of tumor, vasculature and response to anti-angiogenic therapies. As a physicist he works on incorporating biological data in mathematical models to drive predictions. At City of Hope he focusses on targeted radionuclide therapies at both clinical and preclinical levels and uses the generated imaging and non-imaging data to drive mathematical models. 

Feb. 21, 2023, 2:00-2:50 PM Pacific Time

Dr. Eric Mjolsness, UC Irvine

Title: Principled graph dynamics for mathematical modeling of biological morphodynamics

Abstract: Dynamical systems whose number and connectivity of state variables evolve over time are a hallmark of biological systems, and can generally be modeled by spatially embedded graph-local dynamics. These dynamics are expressible by continuous-time rewrite rules in a “dynamical graph grammar” (DGG). We show biological examples in the form of mathematical models of multicellular tissues, and cytoskeletal polymer networks in plants and synapses. We describe a Master Equation operator algebra framework for defining DGG dynamics including stochastic and ordinary differential equation dynamics; derive a Lie algebra for the rule operators; and sketch how several algorithms for simulation can be derived. We address the problems of machine-learned model reduction for approximate changes of scale into and out of DGG models. Time permitting we will place this effort inside a larger Artificial Intelligence perspective on scientific knowledge representation that would be centered on applied mathematics.

Bio: Dr. Eric Mjolsness is a Professor of Computer Science and Mathematics at University of California Irvine. His Ph.D. degree is obtained from Caltech in 1985, with a thesis devoted to neural networks as generative models for pattern recognition. Dr. Mjolsness is an author of many pioneering works in Artificial Intelligence and Neural Networks as well as Systems and Computational Biology including gene/signaling regulatory networks. His current research focus is on modeling languages and methods for plant development and other complex natural systems.

Feb. 14, 2023, 2:00-2:50 PM Pacific Time

Dr. Mykhailo Potomkin, UC Riverside

Title: Motor Protein Transport Along Inhomogeneous Microtubules

Abstract: Networks consisting of many microtubules and actin filaments are key to the transport of material to and from the nucleus of a biological cell. It was hypothesized that defects of active transport along microtubules may be related to many neurodegenerative diseases such as Alzheimer’s disease and Amyotrophic Lateral Sclerosis. One area of need for immediate study is the scenario where the microtubule paths used by motor proteins become congested, obstructed, or defective. In this talk, I will present the agent-based model of motor protein transport with an inhomogeneity describing such defects. First, I will show how the mean-field partial differential equation description was derived from the agent-based model using the multi-scale analysis. Next, an analytic approach to the solution of the derived boundary-value problem will be presented. Finally, I will compare results of Monte-Carlo simulations with analytic solutions. Overall, the model for an inhomogeneous microtubule can inform motor protein dynamics in rough regimes where transport properties are not consistent along given paths. This work was done jointly with Shawn D. Ryan (Cleveland State University), Zachary McCarthy (York University, Canada), and Chase Evans (UC Riverside).

Feb. 7, 2023, 2:00-2:50 PM Pacific Time

Dr. Wayne Hayes, UC Irvine

Title: Predicting Protein Function via Alignment of Protein Interaction Networks

Abstract: Predicting the function of genes, proteins, and other molecular constituents of the cell is a difficult problem whose solution has potentially enormous benefit. The greatest successes in computational methods have come from AI/ML/Deep learning applied to sequence and structure, as well as non-AI methods such as molecular dynamics simulations. While these methods have enjoyed great success recently, the inference path from sequence to structure to function is long and full of pitfalls. Since the function of a molecule is essentially defined by its network of interactions--commonly called a network pathway--network comparison and analysis offers a more direct route to functional prediction. In this talk I will present the first successful functional predictions arising from purely topological cross-species network alignment. I will show how network alignment is capable of transferring knowledge of protein function between species not only without using sequence or structure, but even when no sequence similarity exists and no structural similarity is known. Thus, network alignment produces predictions that are orthogonal to and purely additive to existing prediction methods.

Bio: Wayne Hayes received his degrees in Astrophysics and Computer Science at the University of Toronto. His research spans the scales from molecular dynamics through cells to planets, solar systems, and galaxies. Before coming to UC Irvine, he worked with James Yorke, who shared the Japan Prize with Benoit Mandelbrot for co-developing Chaos Theory. He is currently an Associate Professor of Computer Science at UC Irvine. In his limited spare time, he flies airplanes, rides motorcycles, looks through telescopes, climbs mountains, and wrestles crocodiles.