The topology of biology: Mathematical tools for revealing structure in biological data

Topological Data Analysis (TDA), a relatively new field at the intersection of mathematics and data science, provides a powerful framework for revealing qualitative structure in complex biological data. At its core, TDA uses concepts from geometry and topology to describe the “shape” of data in a rigorous and interpretable way.

In this talk, Dr. Daniel Villarreal, a presidential post doctoral fellow at the School of Mathematical and Statistical Sciences, will introduce persistent homology, the flagship method of TDA, via a specific application in pattern formation on zebrafish skin. He will explain how this method produces biologically relevant descriptors of patterns in an automated, robust and mathematically rigorous way. 

This lecture is part of the Neurodegenerative Disease Research Center Director's Lecture Series.