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Department of Mathematics


Xinfeng Liu awarded NSF Grant

Dr. Xinfeng Liu (PI) and Dr. Hexin Chen (Co-PI)’s project, entitled "Mathematical Modeling, Computational and Experimental Investigation of the Dynamics of Heterogeneity in Breast Cancer", is funded by National Science Foundation (NSF) for three years with direct costs of $140,939 and F/A costs of $69,060 for a total amount of $209,999, with a start date of Monday, April 1, 2019.

Quoted from the research summary:

This research seeks to employ modeling techniques and computational studies to address complex issues arising from tumor growth at the interface of mathematics, chemical engineering and biology. Therefore, principles and techniques from multi-scale models incorporated with new computational algorithms will be employed to achieve the study goals. By integrating complex regulatory networks and spatial distributions of nutrients during tumor growth to control proliferation, differentiation and cell layers of CSCs, the transformative studies and novel methodologies in this project will help revealing the underlying mechanisms to regulate the dynamics and spatial distributions of CSC-derived cell lineages. Hence the outcome of this study may lead to design novel therapeutic strategies for treating cancer development.
Successful completion of this project will also have a signicant impact on public health, as the research findings can be used to develop diagnostics, prognostics, and therapeutics to more specically target cancer stem cells. This project integrates multidisciplinary research with education and will have broader impacts on mathematics, chemical engineering and life sciences. The PIs will mentor students participating in this research project through multidisciplinary training to advance their own scientic knowledge as well as contribute to the wider scientic body. The mathematical and computational toolbox to be developed in this work will enable the PIs to initiate a new project-oriented course, "Multi-scale Modeling and computation for complex biological systems," for better training of both graduate and undergraduate students.