Mathematical methods for biological shape data analysis

Organizers:

Wenjun Zhao (UBC/Wake Forest University), Khanh Dao Duc (UBC)

Description:

Advances in imaging have for the past few years revolutionized our understanding of biological processes, illustrated by the recent mapping of trillions of human cells, or the explosive rate at which thousands of new protein 3D structures are now determined every year. This unprecedented surge of new biological data yields various mathematical problems and challenges at multiple spatial and time scales for interpreting and analyzing morphological shapes and shape dynamics, which finds close connections to machine learning, statistics, and physics. In this context, our proposed mini-symposium focuses on the mathematical, physical, and statistical aspects of shapes that describe the morphologies of biological structures—from molecules and intracellular organelles to cells, tissues, and organs—and how new modeling tools in this field can help elucidate fundamental biological questions. Intended for a diverse audience of mathematicians, physicists, and computational and experimental biologists, the symposium will feature complementary talks covering multiple aspects of imaging data analysis, ranging from the interplay between cell shapes and fate to new discoveries in protein dynamics through Riemannian geometry. To foster collaboration, share insights, and educate junior scientists, we have invited a diverse panel of participants and speakers from various institutes and career stages, including graduate students, postdocs, and faculty members.

Diversity Statement:

Given the highly interdisciplinary nature of the proposed topic, we have invited a diverse panel of participants and speakers from various institutes and backgrounds. We have ensured balanced representation of genders and gender identities to support equity, along with individuals from diverse racial and ethnic backgrounds. Notably, 6/8 of speakers are early-career researchers.