The Mathematical Biology Graduate Student Seminar is a seminar organized by John Fricks and Tim Reluga. The goals are learn about mathematical modelling of biological systems (including statistical and computational models), and to give graduate students more practice presenting their research projects. The seminar participants are students and researchers who know a bit about modelling in general and are very interested in learning more about biology and your particular approach to describing the biology. Presenters should expect frequent interruptions and plan accordingly.

When: 12:10 pm - 1 pm, Tuesdays (sporadically)

Where: 106 McAllister Hall

Students interested in this seminar may find these books interesting.

### Schedule

Date: August 30, 2011

Title: Critical species and the collapse of ecological communities

Speaker: Colin Campbell, Physics

Abstract: Ecosystems suffer a total loss of life if enough species are forcibly removed. In this seminar I will use a model of plant-pollinator ecosystem formation to discuss the properties of ecosystems that suffer complete collapse after the removal of a single species.

Date: September 13, 2011

Title: Analysis of in vitro Co-infections

Speaker: Ivan Simeonov, Statistics

Abstract: The cell response to virus infection is dynamic and is reflected by changes in cell susceptibility to infection. The response of cells to sequential infections with two viruses were evaluated to determine if a primary infection with one strain will impact the ability of cells to be infected with the second as a function of virus strain and time elapsed between the two exposures. Infected cells were then visualized with fluorescent markers, and location of all cells in the tissue culture well were identified using imaging software. Tools from spatial statistics were employed to investigate the likelihood of a cell being infected given its proximity to a cell infected with either the homologous or heterologous virus.

Date: September 20, 2011

Title: Dynamical and Structural Analysis of the T-LGL Leukemia Signaling Network

Abstract: The blood cancer T cell large granular lymphocyte (T-LGL) leukemia is characterized by an abnormal increase in the abundance of a type of white blood cell called T cell. As there is no known curative therapy for this disease, identification of potential therapeutic targets is of utmost importance. In this talk, I will describe a comprehensive dynamical and structural analysis of a network model of this disease. By employing a network reduction technique, we identify fixed points of the system, representing normal and diseased (T-LGL) behavior, and analyze their basins of attraction using an asynchronous Boolean dynamic framework. We identify the state of 54 components of the system, out of which 36 (67%) are corroborated by previous experimental observations and the rest are novel predictions, one of which we validate by follow-up experiments. By deciphering the structure and dynamics of the underlying network, we identify component perturbations that lead to programmed cell death, thereby suggesting several novel candidate therapeutic targets for future experiments.

Date: October 18, 2011

Speaker: Wanyi Zhu, Entomology

Title: Goodbye, Nature vs Nurture: secret life of honeybees

Abstract: A honey bee colony is a population of closely interacting individuals that form a highly complex society. Since 2006, beekeepers worldwide have reported elevated rates of colony losses. As an aid to testing hypotheses for the causes of colony failure and providing suggestions for management actions that are likely to promote recovery of honey bee population, we developed a stage-structured model of honey bee population dynamics to simulate a variety of colony conditions (colony size, intrinsic bee characteristics, resource status). Numerical solutions of the model equations exhibit patterns similar to those observed in honey bee colonies. The simulation results indicate the long-term behavior of a bee population depends on a variety of parameters in different stages of bees and the social control facts related with the brood care and foraging behavior. The model predicts a critical threshold of nurse bee death rate beneath which colonies regulates a stable population size. Also, if the brood care behavior is interrupted beyond the critical threshold rapid population decline is predicted and colony failure is inevitable.

Date: November 1, 2011

Title: Managing Resistance in the ICU: An Evolutionary Approach to Rational Antibiotic Deployment

Speaker: Ells Campbell, Biology

Abstract: We present a population-based model which describes the spread of variably-resistant nosocomial pathogens amongst patients in an intensive care unit of a hospital. This is accomplished via the expansion of a previously published model by introducing pharmacodynamics, pharmacokinetics, and cross-resistance tradeoffs. We depart from this model's predecessors by treating the minimization of resistant-infected patients as secondary to maximizing the proportion of uninfected patients. We confirm that the benefit of a random mixing regimen over periodic cycling is minimal and indicate that strategies which maximize temporal or environmental heterogeneity are inferior to multi-drug cocktails in their ability to exploit resistance-associated fitness tradeoffs; thereby favoring susceptible genotypes and maximizing uninfected.

Date: November 8, 2011

Speaker: Ryan Bradley, UPenn Chemical Engineering

Title: Multiscale modeling of protein-membrane interactions in endocytosis and drug delivery

Abstract: Biological membranes host a multitude of cell signaling processes which are vital to the health of the cell. Defects in these signaling networks play an important role in the development of various cancers. In particular, malfunction in endocytosis can lead to overexpression of membrane-bound receptors and permanent activation of downstream signaling processes. We employ molecular dynamics simulations to understand how proteins remodel the cell membrane at microscopic length scales. At macroscopic length scales, we use a continuum mechanics model to describe membrane geometry, vesicle budding, and curvature-induced protein sorting. Linking these simulations provides a useful method for understanding how molecular factors affect endocytosis. In a related application, multiscale modeling of a nanoparticle binding to endothelial cells provides a framework for designing a targeted drug delivery system. In both cases, we bridge simulations at multiple time and length scales in order to understand the connection between microscopic interactions and cell behavior.

Date: November 15, 2011

Speaker: Guoliang Fang

Title: The Ultimate Extinction Probability of a Biological Population in Heterogenous Environment

Abstract: The development of species introduced to a new environment is of great importance in both ecological and economical sense. During the early settlement phase of the development, smaller populations of the introduced species are more prone to extinction due to the fluctuations caused by stochastic variations. In addition, the spatial heterogeneity of the environment can also significantly affect the establishment of the introduced species through demographic rates. In this presentation, the Ito Diffusion Process with Branching Properties is used to model the settlement of a microorganism population in spatially heterogenous environment. The extinction probability of such process, being a function of starting location and time lapse, satisfies a reaction-diffusion equation with advection term. As a special case, a 1-d environment consisting of alternating good and bad patches has been set up. The effects of patch sizes on the ultimate extinction probability have been investigated. For additional environmental configurations, numerical simulations were adopted.