Data-informed mathematical modeling in cancer and development

Organizers:

Changhan He (University of California, Irvine), Chengyue Wu, University of Texas MD Anderson Cancer Center

Description:

Understanding and representing the complex dynamics of cancer progression and developmental processes is critical for advancing our knowledge of tumor growth, tissue organization, and treatment response. Data-informed mathematical modeling, integrating frameworks such as differential equations, image-processing techniques, and advanced computational methods, provides powerful tools to capture these intricate biological, chemical, and physical interactions. This mini-symposium aims to unite experts and researchers working on innovative mathematical models and computational approaches, leveraging clinical and experimental data for validation. By bridging mathematical modeling with real-world data, we seek to deepen our understanding of both cancer and developmental biology, fostering collaboration to address key challenges in these interconnected fields.

Diversity Statement:

This mini-symposium seeks to promote collaboration and knowledge sharing among researchers and experts in cancer modeling, with a particular focus on ensuring diverse representation by including presenters from underrepresented backgrounds, a range of career stages, and different geographical regions. We propose to cross-list this session with both the MFBM and ONCO Subgroups.