About us
We are a group of researchers studying nutrition, metabolism and epigenetics of cancer cells using interdisciplinary approaches including mathematics, physics, and computer science. We are currently a part of the School of Life Sciences at Southern University of Science and Technology (SUSTech), Shenzhen, China.
Our research
Our research focuses on achieving a quantitative understanding of how nutrition and metabolism affect health outcomes, especially those related to cancer biology. We hope to answer these important questions about metabolism and health using quantitative biology approaches, including mathematical modeling, single-cell and spatial transcriptomics data analysis, and machine learning:
- Can we accurately quantify the spatial and temporal patterns of metabolic fluxes in cells, tissues, and living organisms?
- How are metabolic fluxes regulated by nutrient availability, enzyme activity, and cellular signals?
- What mechanisms lead to the dysregulated metabolism in cancer cells?
- How do metabolic fluxes regulate epigenetics, gene expression, and functional outcomes?
- Can we improve human health by nutritional interventions?
The PI
Ziwei Dai received her Bachelor's degree in applied mathematics from Peking University in 2010, and PhD in physical chemistry from Peking University in 2016. She completed the dissertation on computational modeling of biological networks under the mentorship of Dr. Luhua Lai, and then moved to Duke University to join Dr. Jason Locasale's lab for postdoctoral training. See Ziwei's Curriculum Vitae for further information.
Trained as a mathematician, Ziwei has long been interested in unraveling the design principles of living cells using theoretical and computational approaches. She started her research from the metabolic reactions underlying human inflammatory responses, a pathway named arachidonic acid metabolism. Although she has spent four desperate and frustrating years on this project without any noteworthy publications, she learned, from all these failures, that the integration with data-driven approaches is of extreme importance in computational modeling of biological processes. In the meantime, she read lots of literature on the metabolic reprogramming of cancer cells, which established her interest in cancer metabolism and directed her to her later work on the origin of the Warburg Effect and multi-objective optimality in cancer metabolism, two studies combining mathematical models of cancer metabolism and multi-omics data analysis.
During her postdoctoral training in Jason Locasale's lab at Duke University, she further applied bottom-up mathematical models and data-driven statistical approaches to study the dysregulation of glucose and methionine metabolism in cancer cells. Her findings demonstrate how nutritional inputs affect tumor outcome through modulating metabolism and epigenetics, dissect the complexity in metabolic configurations of single cells in the tumor microenvironment, and offer a reductionist's view on the regulation of metabolic fluxes.
Ziwei likes stargazing, hiking (trails with stairs strongly disfavored), reading, and playing video games. She lives with her cat Snowball.
Contact us
Email:daizw@sustech.edu.cn
Phone: 0755-88018549 (Ziwei's office)