Computational Systems Biology Lab

Principal Investigator: Jason Papin Ph.D.


Our Mission

What do we do?

We aspire to tackle important challenges in the study of metabolic networks that underlie problems in human health & well-being. We perform experiments to understand the systems-level function of these cellular metabolic networks and we develop novel computational tools to integrate these 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 can 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.

new review from @mattagenomics on computational methods to understand #cdiff metabolism and virulence in a forthcoming special issue edited by @TamayoLab and @ShenLabTufts

We support open, reproducible research. Earlier this year, we launched our Code Policy with the aim of increasing the amount of code that is shared with articles published in PLOS Computational Biology - read about all about it here! #OpenScience

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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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An updated genome-scale metabolic network reconstruction of Pseudomonas aeruginosa PA14 to characterize mucin-driven shifts in bacterial metabolism

NPJ Syst Biol Appl. 2021 Oct 8;7(1):37. doi: 10.1038/s41540-021-00198-2.ABSTRACTMucins are present in mucosal membranes throughout the body and play a key role in the microbe clearance and infection prevention. Understanding the metabolic responses of pathogens to mucins will further enable the development of protective approaches against infections. We update the genome-scale metabolic network reconstruction (GENRE) […]

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Novel Drivers of Virulence in Clostridioides difficile Identified via Context-Specific Metabolic Network Analysis

mSystems. 2021 Oct 26;6(5):e0091921. doi: 10.1128/mSystems.00919-21. Epub 2021 Oct 5. ABSTRACT The pathogen Clostridioides difficile causes toxin-mediated diarrhea and is the leading cause of hospital-acquired infection in the United States. Due to growing antibiotic resistance and recurrent infection, targeting C. difficile metabolism presents a new approach to combat this infection. Genome-scale metabolic network reconstructions (GENREs) […]

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Perinatal Outcomes of Asynchronous Influenza Vaccination, Ceará, Brazil, 2013-2018

Emerg Infect Dis. 2021;27(9):2409-2420. doi: 10.3201/eid2709.203791. ABSTRACT In Ceará, Brazil, seasonal influenza transmission begins before national annual vaccination campaigns commence. To assess the perinatal consequences of this misalignment, we tracked severe acute respiratory infection (SARI), influenza, and influenza immunizations during 2013-2018. Among 3,297 SARI cases, 145 (4.4%) occurred in pregnant women. Statewide vaccination coverage was […]

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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

Send a Message

[email protected]