Week of January 29 - January 25
Applied and Computational Mathematics
Topic: DNA methylation-based aging biomarkers in health and disease
Mary Sehl | UCLA
Abstract: DNA methylation-based estimates of age are strongly correlated with chronologic age across many cell types and tissues. Importantly, these biologic aging estimates are accelerated in disease states, and predictive of both lifespan and healthspan. Recent evidence suggests that female breast tissue ages faster than other parts of the body in healthy women, based on the Horvath pan-tissue epigenetic clock. Estrogens are thought to contribute to breast cancer risk through cell cycling and accelerated breast aging. We hypothesize that epigenetic breast aging is driven by lifetime estrogen exposure. In this talk, we will review the development and key features of several epigenetic clocks including Horvath’s pan-tissue clock and the Hannum clock, as well as second generation clocks including the Phenotypic age, Grim age, and Skin and Blood age clocks. We will describe findings from a recent study examining associations between hormonal factors (including earlier age at menarche, and body mass index) and these epigenetic aging measures in healthy women. We will further describe additional applications of peripheral blood methylation age estimates to study biologic age acceleration in HIV-infected men pre- and post-initiation of antiretroviral therapy, and in early stage breast cancer survivors undergoing radiotherapy and chemotherapy.
Zoom access:
Meeting ID:
Zoom meeting starts at 3:30pm
Colloquium
Topic: TBA
Kelsey Gasior | Florida State
Abstract: TBA
Join us:
Zoom access: Contact mbrown2@math.tulane.edu
Time: 3:30pm
Algebra and Combinatorics
Topic: Stable Harbourne-Huneke containment and Chudnovsky's Conjecture
Sankhaneel Bisui | Tulane University
Abstract:
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Zoom access:
Time: 3:30pm
Colloquium
Topic: Modeling and analysis of complex systems — with a basis in zebrafish patterns
Alexandria Volkening | Northwestern University
Abstract: Many natural and social phenomena involve individual agents coming together to create group dynamics, whether they are cells in a skin pattern, voters in an election, or pedestrians in a crowded room. Here I will focus on the specific example of pattern formation in zebrafish, which are named for the dark and light stripes that appear on their bodies and fins. Mutant zebrafish, on the other hand, feature different skin patterns, including spots and labyrinth curves. All these patterns form as the fish grow due to the interactions of tens of thousands of pigment cells. The longterm motivation for my work is to better link genes, cell behavior, and visible animal characteristics — I seek to identify the specific alterations to cell interactions that lead to mutant patterns. Toward this goal, I develop agent-based models to simulate pattern formation and make experimentally testable predictions. In this talk, I will overview my models and highlight future directions. Because agent-based models are not analytically tractable using traditional techniques, I will also discuss the topological methods that we have developed to quantitatively describe cell-based patterns, as well as the associated nonlocal continuum limits of my models.
Join us:
Zoom access: Contact mbrown2@math.tulane.edu
Time: 3:30pm
