Systems Biology & Computational Bioengineering
Tackling complex challenges in human health requires the systematic analysis of molecular, cellular, and multi-cellular processes in a quantitative framework. Rich datasets emerge from the development and application of cutting-edge experimental methods that deeply interrogate cell-tissue-organ physiology. Integration of these “Big Data” can only be achieved through computational models that are scalable, flexible, and quantitatively rigorous. Biomedical engineers are uniquely qualified to combine large-scale data acquisition and model-driven analysis at a systems level.
Systems Biology & Computational Bioengineering is a distinguished and defining strength of Biomedical Engineering at UVA. The department boasts an array of dual experimental-computational faculty with interests in cardiovascular, musculoskeletal, and developmental biology, infectious disease, and cancer. This research focus also has a strong emphasis on methods development—experimental, computational, and technological—with the belief that new tools can enable deeper a systems-level understanding of disease.
Silvia Salinas Blemker: multi-scale modeling of skeletal muscle mechanics, injury, remodeling, and disease
Mete Civelek: systems genetics approaches to understand cellular and organismal pathways leading to cardiometabolic disorders, network modeling of gene co-regulation, validation of computational predictions in cells and organisms
Jeff Holmes: multi-scale modeling of heart mechanics, growth, and remodeling
Kevin Janes: design of high-throughput and multiplex assays for intracellular signaling and transcriptional regulation; data-driven modeling of signal-transduction and gene-expression networks
Jason Papin: metabolic and regulatory network reconstruction and analysis with applications in infectious disease and cancer
Shayn Peirce-Cottler: combinations of cytokines, growth factors, and stem cells in blood vessel growth and inflammation, multi-scale computational modeling of cell interactions during tissue remodeling
Jeff Saucerman: multi-scale modeling of signaling networks and their regulation of cardiac contractility, remodeling, and heart failure
Eli Zunder: single-cell analysis of pluripotent stem cell reprogramming and differentiation; high-dimensional modeling of cell population transitions and lineage trajectories
Chris Deppmann: competitive programs underlying the assembly and disassembly of the nervous system during development and disease; design and optimization of novel reporters, actuators, and microfluidic culture platforms
Peter Kasson: network approaches to conformational dynamics in infectious disease; large-scale computing; engineering approaches to membrane biology; viral infection and bacterial drug resistance
Nathan Sheffield: Computational cancer epigenomics, Single-cell sequencing analysis, Gene regulation and chromatin structure