Changde Cheng

I am an assistant professor in the Stem Cell Biology Program and the Institute for Cancer Outcomes and Survivorship at the University of Alabama at Birmingham. My research focuses on computational and evolutionary genomics, particularly in relation to stem cells involved in aging, critical illness, and cancer. I aim to understand how cellular dynamics relate to the initiation, progression, and treatment outcomes of these diseases.

During my postdoctoral research, I worked with Mark Kirkpatrick and David Houle, studying sexual antagonistic selection, the evolution of sexual differentiation, and aging. Prior to that, I completed my Ph.D. at the University of Notre Dame, under the guidance of Nora Besansky, where I researched speciation, chromosomal evolution, ecological genomics, and evolutionary genomics. Before pursuing my Ph.D., I worked with Charles Taylor at UCLA on evolutionary genetics. I earned my B.S. degree in cell biology and genetics from Peking University.


Therapy Design and Engineering

From single-cell perturbations to patient-ready strategies, we engineer combination therapies by mapping epistasis, inferring causal control, and optimizing interventions with mechanism-informed AI.

We investigate how genes, pathways, and cell types coordinate cellular decision-making and organization. Our research develops computational methods for Perturb-seq and single-cell multi-omics data to map multidimensional interaction landscapes and quantify epistatic effects at single-cell resolution.

We integrate experimental datasets with dynamical models to infer causal relationships in biological networks. This framework identifies synergistic versus antagonistic interactions and pinpoints critical control nodes governing cellular behavior.

We translate these insights into design principles for combinatorial interventions—CRISPR strategies, drug combinations, and cellular therapies. Recent work includes retinal vascular repair using iPSC-derived CD34⁺ progenitor and endothelial colony-forming cells.

Our approach extends to cancer biology and immunology, modeling tumor microenvironments, predicting resistance pathways, and designing therapeutic strategies that account for evolutionary dynamics.

Projects

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