Computational Systems Biology Lab

Principal Investigator: Jason Papin Ph.D.

Our Mission

What do we do?

We aspire to tackle important questions in the study of metabolic networks that underlie challenges in human health & well-being. We perform experiments to understand the systems-level function of cellular metabolic networks and we develop novel computational tools to integrate high-throughput data in order to predict how cells respond to environmental & genetic perturbations. We perform further experiments to validate and improve these computational models. With increased predictive ability, we gain an understanding of mechanisms of metabolism that are critical in public health and identify potential strategies and interventions. Our efforts in this research area are always guided by clear ethical principles.  As we engage in this research, we will make important advances in the health and well-being of society.

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The Papin Lab

Understanding biochemical networks will lead to revolutionary advances in medicine and biotechnology.

There is a pressing need for reconstructing and analyzing the biochemical networks that orchestrate cellular processes. Understanding how these biochemical networks function (and malfunction) will lead to revolutionary advances in medicine, biotechnology, and the understanding of fundamental biological processes.

The Computational Systems Biology Laboratory (CSBL) at the University of Virginia uses computational and experimental approaches to characterize biological systems relevant to human disease. In particular, we reconstruct integrated cellular networks and develop tools to analyze their properties. The analysis of these networks requires sophisticated computing capabilities, experimental methods, and mathematical techniques.

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Recent Publications

View some of the Papin Lab's most recent published works. A more complete list of our published works can be found below or by visiting Dr. Papin's PubMed page found on the Publications page.

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Network analysis of toxin production in Clostridioides difficile identifies key metabolic dependencies

PLoS Comput Biol. 2023 Apr 26;19(4):e1011076. doi: 10.1371/journal.pcbi.1011076. Online ahead of print. ABSTRACT Clostridioides difficile pathogenesis is mediated through its two toxin proteins, TcdA and TcdB, which induce intestinal epithelial cell death and inflammation. It is possible to alter C. difficile toxin production by changing various metabolite concentrations within the extracellular environment. However, it is […]

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Metabolic modeling of sex-specific tissue predicts mechanisms of differences in toxicological responses

bioRxiv. 2023 Feb 7:2023.02.07.527430. doi: 10.1101/2023.02.07.527430. Preprint. ABSTRACT Male subjects in animal and human studies are disproportionately used for toxicological testing. This discrepancy is evidenced in clinical medicine where females are more likely than males to experience liver-related adverse events in response to xenobiotics. While previous work has shown gene expression differences between the sexes, […]

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Identifying metabolic shifts in Crohn’s disease using’ omics-driven contextualized computational metabolic network models

Sci Rep. 2023 Jan 5;13(1):203. doi: 10.1038/s41598-022-26816-5. ABSTRACT Crohn’s disease (CD) is a chronic inflammatory disease of the gastrointestinal tract. A clear gap in our existing CD diagnostics and current disease management approaches is the lack of highly specific biomarkers that can be used to streamline or personalize disease management. Comprehensive profiling of metabolites holds […]

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415 Lane Road, Room 2041
Charlottesville, VA 22903

Contact Information

(434) 924-8195
Computational lab:
(434) 982-6267
Computational lab 2nd line:
(434) 982-6269
Wet lab:
(434) 924-8640

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Computational Systems Biology Laboratory; The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia.

Contact Info

The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia

  • Email:
  • Phone (434) 924-8195