https://illinois.zoom.us/j/84907159401?pwd=JboBtq30vntVuEpj8s3yYfAdwlb258.1
Title: Applied Topology, Topological Spectral Theory, and Machine Learning Models for Biological Applications
Abstract: Topological methods provide powerful tools for analyzing complex, high-dimensional data. In this talk, I will present recent advances in Topological Deep Learning (TDL) and their applications to key problems in bioscience. A central concept in TDL is Persistent Spectral Graphs (PSGs), a method in Topological Data Analysis (TDA) that is designed to capture intricate topological changes and homotopy shape evolution information for high-dimensional biological data. I will demonstrate how PSG-based representations of biomolecules can be incorporated into AI pipelines to yield TDL models with strong predictive power. Applications span multiple biological domains, including forecasting the emergence of new COVID-19 variants, inferring RNA secondary structure motifs, and improving model selection for peptide–protein complexes predicted by AlphaFold2 and AlphaFold3.
The Midwest Mathematical Biology Seminar will be a series of virtual talks on mathematical biology featuring speakers from the Midwest region and beyond. All areas of mathematical biology will be represented in the seminar series, and a goal for this seminar is to build connections and foster research collaborations.
More information - https://sites.google.com/view/midwest-mathbio-seminar/home
Tiffany Leighton
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