Contact
Office
(434) 924-5095
Location
MR5 Room 2111 (inside the lab)
Lab
​MR5 Room 2213/2207
Box 800759 Health System
Charlottesville, VA 22908

Jeff Saucerman

Professor, Biomedical Engineering
Contact
Office
(434) 924-5095
Location
MR5 Room 2111 (inside the lab)
Lab
​MR5 Room 2213/2207
Box 800759 Health System
Charlottesville, VA 22908
Google Scholar ResearchGate PubMed Cardiac Systems Biology Group

About

Our lab combines computational modeling and high-throughput experiments to discover molecular networks and drugs that control cardiac remodeling. Our experimental approaches include high-throughput microscopy and -omic profiling of various types of primary and induced pluripotent stem cell (iPSC)-derived cardiac cells (e.g. cardiomyocytes, fibroblasts, macrophages). Our computational approaches include large-scale modeling of signaling/gene regulatory networks, machine learning on -omic data, and mining of electronic health records. Specific application areas include:

  • cardiac hypertrophy, survival, and regeneration
  • cardiac development
  • inflammation-fibrosis coupling

Education

Ph.D. in Bioengineering, University of California San Diego, 2005

​B.S. in Engineering Science, Pennsylvania State University, 2000

We are mapping the complex networks that control heart function and failure

Jeffrey Saucerman Professor of Biomedical Engineering

Research Interests

Systems Biology
Cardiovascular Disease
Regenerative Medicine
Machine Learning / AI / Data Science
Cellular and Molecular Engineering
Inflammation-Fibrosis

Selected Publications

Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts. Proc Natl Acad Sci (2024) Anders R Nelson 1, Steven L Christiansen 1 2, Kristen M Naegle 1, Jeffrey J Saucerman 1
Abstract
Virtual drug screen reveals context-dependent inhibition of cardiomyocyte hypertrophy. British Journal of Pharmacology (2023) Taylor G Eggertsen 1 2, Jeffrey J Saucerman 1 2
Abstract
Brahma safeguards canalization of cardiac mesoderm differentiation. Nature (2022) Hota SK, Rao KS, Blair AP, Khalilimeybodi A, Hu KM, Thomas R, So K, Kameswaran V, Xu J, Polacco BJ, Desai RV, Chatterjee N, Hsu A, Muncie JM, Blotnick AM, Winchester SAB, Weinberger LS, Hüttenhain R, Kathiriya IS, Krogan NJ, Saucerman JJ, Bruneau BG.
Abstract

Courses Taught

BME 2315 Computational Biomedical Engineering
BME 4550 Systems Bioengineering Modeling and Experimentation
BME 8315 Systems Bioengineering and Multi-Scale Models

Awards

Fellow of the American Institute for Medical and Biological Engineering 2023
UVA BME Graduate Mentoring Award 2023
Vivian Pinn Scholars Award 2018
Fellow of the American Heart Association 2014
NSF CAREER Award 2013
Dean's Excellence in Teaching Award 2012

Featured Grants & Projects

Cardiac hypertrophy Dozens of pathways are implicated in cardiac myocyte growth, but little is known about the quantitative contribution of these pathways to myocyte shape, reversibility, sarcomeric organization, or many other factors affecting the progression of heart failure. We are combining high-throughput microscopy, automated image processing, and large-scale network modeling to address these challenges.
Cardiac inflammation and extracellular matrix remodeling Cardiac macrophages and fibroblasts play important roles in inflammation and wound healing following cardiac injury. Yet systems and therapeutic approaches targeting these cells have been limited. We are collaborating with investigators at UVA and externally to reconstruct the molecular networks in fibroblasts and macrophages in the context of myocardial infarction.
Cardiac regeneration While cardiac regeneration was once thought to be limited to organisms such newts and zebrafish, recent studies have demonstrated that mammals also have some regenerative capacity. We are combining genomic and high-throughput microscopy experiments with computational models to map the molecular networks and identify compounds that stimulate cardiac myocyte proliferation.