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Category Archives: Published Works

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September 10 2020
  • Published Works

Clostridioides difficile: Sometimes It Pays To Be Difficult

Cell Host Microbe. 2020 Sep 9;28(3):358-359. doi: 10.1016/j.chom.2020.08.010. ABSTRACT In this issue of Cell Host & Microbe, publications from Bushman et al. (2020) and Knippel et al. (2020) outline elements of host epithelial damage or inflammation that Clostridioides difficile subverts, enabling continued growth. These mechanisms provide insight into how this important pathogen influences the gut […]

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August 27 2020
  • Published Works

Community standards to facilitate development and address challenges in metabolic modeling

Mol Syst Biol. 2020 Aug;16(8):e9235. doi: 10.15252/msb.20199235. ABSTRACT Standardization of data and models facilitates effective communication, especially in computational systems biology. However, both the development and consistent use of standards and resources remain challenging. As a result, the amount, quality, and format of the information contained within systems biology models are not consistent and therefore […]

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July 2 2020
  • Published Works

Minimum Bactericidal Concentration of Ciprofloxacin to Pseudomonas aeruginosa Determined Rapidly Based on Pyocyanin Secretion

Sens Actuators B Chem. 2020 Jun 1;312:127936. doi: 10.1016/j.snb.2020.127936. Epub 2020 Mar 4. ABSTRACT Infections due to Pseudomonas aeruginosa (P. aeruginosa) often exhibit broad-spectrum resistance and persistence to common antibiotics. Persistence is especially problematic with immune-compromised subjects who are unable to eliminate the inhibited bacteria. Hence, antibiotics must be used at the appropriate minimum bactericidal […]

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May 20 2020
  • Published Works

Improving reproducibility in computational biology research

PLoS Comput Biol. 2020 May 19;16(5):e1007881. doi: 10.1371/journal.pcbi.1007881. eCollection 2020 May. NO ABSTRACT PMID:32427998 | PMC:PMC7236972 | DOI:10.1371/journal.pcbi.1007881

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April 30 2020
  • Published Works

Medusa: Software to build and analyze ensembles of genome-scale metabolic network reconstructions

PLoS Comput Biol. 2020 Apr 29;16(4):e1007847. doi: 10.1371/journal.pcbi.1007847. eCollection 2020 Apr. ABSTRACT Uncertainty in the structure and parameters of networks is ubiquitous across computational biology. In constraint-based reconstruction and analysis of metabolic networks, this uncertainty is present both during the reconstruction of networks and in simulations performed with them. Here, we present Medusa, a Python […]

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April 17 2020
  • Published Works

Transcriptome-guided parsimonious flux analysis improves predictions with metabolic networks in complex environments

PLoS Comput Biol. 2020 Apr 16;16(4):e1007099. doi: 10.1371/journal.pcbi.1007099. eCollection 2020 Apr. ABSTRACT The metabolic responses of bacteria to dynamic extracellular conditions drives not only the behavior of single species, but also entire communities of microbes. Over the last decade, genome-scale metabolic network reconstructions have assisted in our appreciation of important metabolic determinants of bacterial physiology. […]

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April 9 2020
  • Published Works

Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing

Nat Biotechnol. 2020 Apr;38(4):504. doi: 10.1038/s41587-020-0477-4. ABSTRACT An amendment to this paper has been published and can be accessed via a link at the top of the paper. PMID:32265554 | PMC:PMC7138757 | DOI:10.1038/s41587-020-0477-4

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March 4 2020
  • Published Works

MEMOTE for standardized genome-scale metabolic model testing

Nat Biotechnol. 2020 Mar;38(3):272-276. doi: 10.1038/s41587-020-0446-y. NO ABSTRACT PMID:32123384 | PMC:PMC7082222 | DOI:10.1038/s41587-020-0446-y

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February 7 2020
  • Published Works

Core Competencies for Undergraduates in Bioengineering and Biomedical Engineering: Findings, Consequences, and Recommendations

Ann Biomed Eng. 2020 Mar;48(3):905-912. doi: 10.1007/s10439-020-02468-2. Epub 2020 Feb 5. ABSTRACT This paper provides a synopsis of discussions related to biomedical engineering core curricula that occurred at the Fourth BME Education Summit held at Case Western Reserve University in Cleveland, Ohio in May 2019. This summit was organized by the Council of Chairs of […]

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January 14 2020
  • Published Works

Guiding the Refinement of Biochemical Knowledgebases with Ensembles of Metabolic Networks and Machine Learning

Cell Syst. 2020 Jan 22;10(1):109-119.e3. doi: 10.1016/j.cels.2019.11.006. Epub 2020 Jan 8. ABSTRACT Mechanistic models explicitly represent hypothesized biological knowledge. As such, they offer more generalizability than data-driven models. However, identifying model curation efforts that improve performance for mechanistic models is nontrivial. Here, we develop a solution to this problem for genome-scale metabolic models. We generate […]

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Recent Posts

  • Model-driven characterization of functional diversity of Pseudomonas aeruginosa clinical isolates with broadly representative phenotypes
  • Systems-ecology designed bacterial consortium protects from severe Clostridioides difficile infection
  • Metabolic modeling of sex-specific liver tissue suggests mechanism of differences in toxicological responses
  • The blossoming of methods and software in computational biology
  • Transcriptome-guided metabolic network analysis reveals rearrangements of carbon flux distribution in Neisseria gonorrhoeae during neutrophil co-culture
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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.

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

  • Email: papinlab@virginia.edu
  • Phone (434) 924-8195

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  • Meet Our Team
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