Furtado, K. L., Plott, L., Markovetz, M., Powers, D., Wang, H., Hill, D. B., . . . Tamayo, R. (2024). Clostridioides difficile-mucus interactions encompass shifts in gene expression, metabolism, and biofilm formation. MSPHERE. doi:10.1128/msphere.00081-24

Islam, M. M., Kolling, G. L., Glass, E. M., Goldberg, J. B., & Papin, J. A. (2024). Model-driven characterization of functional diversity of Pseudomonas aeruginosa clinical isolates with broadly representative phenotypes.. Microbial genomics, 10(6). doi:10.1099/mgen.0.001259

Dougherty, B. V., Moore, C. J., Rawls, K. D., Jenior, M. L., Chun, B., Nagdas, S., . . . Papin, J. A. (2024). Identifying metabolic adaptations characteristic of cardiotoxicity using paired transcriptomics and metabolomics data integrated with a computational model of heart metabolism. PLOS COMPUTATIONAL BIOLOGY, 20(2). doi:10.1371/journal.pcbi.1011919

Mac Gabhann, F., Pitzer, V. E., & Papin, J. A. (2023). The blossoming of methods and software in computational biology. PLOS COMPUTATIONAL BIOLOGY, 19(8). doi:10.1371/journal.pcbi.1011390

Moore, C. J., Holstege, C. P., & Papin, J. A. (2023). Metabolic modeling of sex-specific liver tissue suggests mechanism of differences in toxicological responses.. PLoS computational biology, 19(8), e1010927. doi:10.1371/journal.pcbi.1010927

Jenior, M. L., Glass, E. M., & Papin, J. A. (2023). Reconstructor: a COBRApy compatible tool for automated genome-scale metabolic network reconstruction with parsimonious flux-based gap-filling. BIOINFORMATICS, 39(6). doi:10.1093/bioinformatics/btad367

Powers, D. A., Jenior, M., Kolling, G., & Papin, J. (2023). Network analysis of toxin production in Clostridioides difficile identifies key metabolic dependencies. PLOS COMPUTATIONAL BIOLOGY, 19(4). doi:10.1371/journal.pcbi.1011076

Moore, C. J., Holstege, C. P., & Papin, J. A. (2023). Metabolic modeling of sex-specific tissue predicts mechanisms of differences in toxicological responses.. bioRxiv. doi:10.1101/2023.02.07.527430

Fernandes, P., Sharma, Y., Zulqarnain, F., McGrew, B., Shrivastava, A., Ehsan, L., . . . Syed, S. (2023). Identifying metabolic shifts in Crohn's disease using' omics-driven contextualized computational metabolic network models. SCIENTIFIC REPORTS, 13(1). doi:10.1038/s41598-022-26816-5

Dillard, L. R., Glass, E. M., Lewis, A. L., Thomas-White, K., & Papin, J. A. (2023). Metabolic Network Models of the Gardnerella Pangenome Identify Key Interactions with the Vaginal Environment. MSYSTEMS, 8(1). doi:10.1128/msystems.00689-22

Papin, J. A., Keim-Malpass, J., & Syed, S. (2022). Ten simple rules for launching an academic research career. PLOS COMPUTATIONAL BIOLOGY, 18(12). doi:10.1371/journal.pcbi.1010689

Smith, A. B., Jenior, M. L., Keenan, O., Hart, J. L., Specker, J., Abbas, A., . . . Zackular, J. P. (2022). Enterococci enhance Clostridioides difficile pathogenesis. NATURE, 611(7937), 780-+. doi:10.1038/s41586-022-05438-x

Jenior, M. L., Dickenson, M. E., & Papin, J. A. (2022). Genome-scale metabolic modeling reveals increased reliance on valine catabolism in clinical isolates of Klebsiella pneumoniae. NPJ SYSTEMS BIOLOGY AND APPLICATIONS, 8(1). doi:10.1038/s41540-022-00252-7

Fawad, J. A., Luzader, D. H., Hanson, G. F., Moutinho Jr, T. J., McKinney, C. A., Mitchell, P. G., . . . Moore, S. R. (2022). Histone Deacetylase Inhibition by Gut Microbe-Generated Short-Chain Fatty Acids Entrains Intestinal Epithelial Circadian Rhythms. GASTROENTEROLOGY, 163(5), 1377-+. doi:10.1053/j.gastro.2022.07.051

Dillard, L. R., Wase, N., Ramakrishnan, G., Park, J. J., Sherman, N. E., Carpenter, R., . . . Papin, J. A. (2022). Leveraging metabolic modeling to identify functional metabolic alterations associated with COVID-19 disease severity. METABOLOMICS, 18(7). doi:10.1007/s11306-022-01904-9

Cadwallader, L., Mac Gabhann, F., Papin, J., & Pitzer, V. E. (2022). Advancing code sharing in the computational biology community. PLOS COMPUTATIONAL BIOLOGY, 18(6). doi:10.1371/journal.pcbi.1010193

Moutinho, T. J. J., Powers, D. A., Hanson, G. F., Levy, S., Baveja, R., Hefner, I., . . . Hourigan, S. K. (2022). Fecal sphingolipids predict parenteral nutrition-associated cholestasis in the neonatal intensive care unit. JOURNAL OF PARENTERAL AND ENTERAL NUTRITION, 46(8), 1903-1913. doi:10.1002/jpen.2374

Carey, M., Medlock, G., Stolarczyk, M., Petri Jr, W., Guler, J., & Papin, J. (2022). Comparative analyses of parasites with a comprehensive database of geno-scale metabolic models. PLOS COMPUTATIONAL BIOLOGY, 18(2). doi:10.1371/journal.pcbi.1009870

Moutinho Jr, T. A., Neubert, B., Jenior, M., & Papin, J. (2022). Quantifying cumulative phenotypic and genomic evidence for procedural generation of metabolic network reconstructions. PLOS COMPUTATIONAL BIOLOGY, 18(2). doi:10.1371/journal.pcbi.1009341

Jenior, M. L., & Papin, J. A. (2022). Computational approaches to understanding Clostridioides difficile metabolism and virulence. CURRENT OPINION IN MICROBIOLOGY, 65, 108-115. doi:10.1016/j.mib.2021.11.002

Payne, D. D., Renz, A., Dunphy, L. J., Lewis, T., Drager, A., & Papin, J. A. (2021). An updated genome-scale metabolic network reconstruction of Pseudomonas aeruginosa PA14 to characterize mucin-driven shifts in bacterial metabolism. NPJ SYSTEMS BIOLOGY AND APPLICATIONS, 7(1). doi:10.1038/s41540-021-00198-2

Jenior, M. L., Leslie, J. L., Powers, D. A., Garrett, E. M., Walker, K. A., Dickenson, M. E., . . . Papin, J. A. (2021). Novel Drivers of Virulence in Clostridioides difficile Identified via Context-Specific Metabolic Network Analysis. MSYSTEMS, 6(5). doi:10.1128/mSystems.00919-21

Dunphy, L. J., Kolling, G. L., Jenior, M. L., Carroll, J., Attai, A. E., Farnoud, F., . . . Papin, J. A. (2021). Multidimensional Clinical Surveillance of Pseudomonas aeruginosa Reveals Complex Relationships between Isolate Source, Morphology, and Antimicrobial Resistance. MSPHERE, 6(4). doi:10.1128/mSphere.00393-21

Dunphy, L. J., Grimes, K. L., Wase, N., Kolling, G. L., & Papin, J. A. (2021). Untargeted Metabolomics Reveals Species-Specific Metabolite Production and Shared Nutrient Consumption by Pseudomonas aeruginosa and Staphylococcus aureus. MSYSTEMS, 6(3). doi:10.1128/mSystems.00480-21

Carey, M. A., Medlock, G. L., Alam, M., Kabir, M., Uddin, M. J., Nayak, U., . . . Gilchrist, C. A. (2021). Megasphaera in the Stool Microbiota Is Negatively Associated With Diarrheal Cryptosporidiosis. CLINICAL INFECTIOUS DISEASES, 73(6), E1242-E1251. doi:10.1093/cid/ciab207

Dougherty, B. V., Rawls, K. D., Kolling, G. L., Vinnakota, K. C., Wallqvist, A., & Papin, J. A. (2021). Identifying functional metabolic shifts in heart failure with the integration of omics data and a heart-specific, genome-scale model. CELL REPORTS, 34(10). doi:10.1016/j.celrep.2021.108836

Cadwallader, L., Papin, J. A., Mac Gabhann, F., & Kirk, R. (2021). Collaborating with our community to increase code sharing. PLOS COMPUTATIONAL BIOLOGY, 17(3). doi:10.1371/journal.pcbi.1008867

Grimes, K. L., Dunphy, L. J., Kolling, G. L., Papin, J. A., & Colosi, L. M. (2021). Algae-mediated treatment offers apparent removal of a model antibiotic resistance gene. ALGAL RESEARCH-BIOMASS BIOFUELS AND BIOPRODUCTS, 60. doi:10.1016/j.algal.2021.102540

Jose, Q. F., Junior, F. S., Lima, T. B. R., Viana, V. A. F., Burgoa, J. S. V., Soares, A. M., . . . Lima, A. A. M. (2021). Perinatal Outcomes of Asynchronous Influenza Vaccination, Ceara, Brazil, 2013-2018. EMERGING INFECTIOUS DISEASES, 27(9), 2409-2420. doi:10.3201/eid2709.203791

Dillard, L. R., Payne, D. D., & Papin, J. A. (2021). Mechanistic models of microbial community metabolism. MOLECULAR OMICS, 17(3), 365-375. doi:10.1039/d0mo00154f

Rawls, K. D., Dougherty, B. V., Vinnakota, K. C., Pannala, V. R., Wallqvist, A., Kolling, G. L., & Papin, J. A. (2021). Predicting changes in renal metabolism after compound exposure with a genome-scale metabolic model. TOXICOLOGY AND APPLIED PHARMACOLOGY, 412. doi:10.1016/j.taap.2020.115390

Jenior, M. L., & Papin, J. A. (2020). Clostridioides difficile: Sometimes It Pays To Be Difficult. CELL HOST & MICROBE, 28(3), 358-359. doi:10.1016/j.chom.2020.08.010

Carey, M. A., Draeger, A., Beber, M. E., Papin, J. A., & Yurkovich, J. T. (2020). Community standards to facilitate development and address challenges in metabolic modeling. MOLECULAR SYSTEMS BIOLOGY, 16(8). doi:10.15252/msb.20199235

Papin, J. A., Mac Gabhann, F., Sauro, H. M., Nickerson, D., & Rampadarath, A. (2020). Improving reproducibility in computational biology research. PLOS COMPUTATIONAL BIOLOGY, 16(5). doi:10.1371/journal.pcbi.1007881

Hourigan, S. K., Moutinho, T. J. J., Berenz, A., Papin, J., Guha, P., Bangiolo, L., . . . Moore, S. R. (2020). Gram-negative Microbiota Blooms in Premature Twins Discordant for Parenteral Nutrition-associated Cholestasis. JOURNAL OF PEDIATRIC GASTROENTEROLOGY AND NUTRITION, 70(5), 640-644. doi:10.1097/MPG.0000000000002617

Medlock, G. L., Moutinho, T. J., & Papin, J. A. (2020). Medusa: Software to build and analyze ensembles of genome-scale metabolic network reconstructions. PLOS COMPUTATIONAL BIOLOGY, 16(4). doi:10.1371/journal.pcbi.1007847

Jenior, M. L., Moutinho, T. J. J., Dougherty, B. V., & Papin, J. A. (2020). Transcriptome-guided parsimonious flux analysis improves predictions with metabolic networks in complex environments. PLOS COMPUTATIONAL BIOLOGY, 16(4). doi:10.1371/journal.pcbi.1007099

Lieven, C., Beber, M. E., Olivier, B. G., Bergmann, F. T., Ataman, M., Babaei, P., . . . Zhang, C. (2020). Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing.. Nature biotechnology, 38(4), 504. doi:10.1038/s41587-020-0477-4

Liu, Y., Moore, J. H., Kolling, G. L., McGrath, J. S., Papin, J. A., & Swami, N. S. (2020). Minimum bactericidal concentration of ciprofloxacin to Pseudomonas aeruginosa determined rapidly based on pyocyanin secretion. SENSORS AND ACTUATORS B-CHEMICAL, 312. doi:10.1016/j.snb.2020.127936

Lieven, C., Beber, M. E., Olivier, B. G., Bergmann, F. T., Ataman, M., Babaei, P., . . . Zhang, C. (2020). MEMOTE for standardized genome-scale metabolic model testing. NATURE BIOTECHNOLOGY, 38(3), 272-276. doi:10.1038/s41587-020-0446-y

White, J. A., Gaver, D. P., Butera, R. J. J., Choi, B., Dunlop, M. J., Grande-Allen, K. J., . . . Lee, A. P. (2020). Core Competencies for Undergraduates in Bioengineering and Biomedical Engineering: Findings, Consequences, and Recommendations. ANNALS OF BIOMEDICAL ENGINEERING, 48(3), 905-912. doi:10.1007/s10439-020-02468-2

Medlock, G. L., & Papin, J. A. (2020). Guiding the Refinement of Biochemical Knowledgebases with Ensembles of Metabolic Networks and Machine Learning. CELL SYSTEMS, 10(1), 109-+. doi:10.1016/j.cels.2019.11.006

Dougherty, B. V., & Papin, J. A. (2020). Systems biology approaches help to facilitate interpretation of cross-species comparisons. CURRENT OPINION IN TOXICOLOGY, 23-24, 74-79. doi:10.1016/j.cotox.2020.06.002

Rawls, K., Dougherty, B. V., & Papin, J. (2020). Metabolic Network Reconstructions to Predict Drug Targets and Off-Target Effects. METABOLIC FLUX ANALYSIS IN EUKARYOTIC CELLS: METHODS AND PROTOCOLS, 2088, 315-330. doi:10.1007/978-1-0716-0159-4_14

Pannala, V. R., Vinnakota, K. C., Estes, S. K., Trenary, I., O'Brien, T. P., Printz, R. L., . . . Wallqvist, A. (2020). Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity. TOXICOLOGICAL SCIENCES, 173(2), 293-312. doi:10.1093/toxsci/kfz228

Carey, M., Medlock, G., Stolarczyk, M., Petri, W., Guler, J., & Papin, J. (2019). Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models. doi:10.1101/772467

Rawls, K. D., Blais, E. M., Dougherty, B. V., Vinnakota, K. C., Pannala, V. R., Wallqvist, A., . . . Papin, J. A. (2019). Genome-Scale Characterization of Toxicity-Induced Metabolic Alterations in Primary Hepatocytes. TOXICOLOGICAL SCIENCES, 172(2), 279-291. doi:10.1093/toxsci/kfz197

Grimes, K. L., Dunphy, L. J., Loudermilk, E. M., Melara, A. J., Kolling, G. L., Papin, J. A., & Colosi, L. M. (2019). Evaluating the efficacy of an algae-based treatment to mitigate elicitation of antibiotic resistance. CHEMOSPHERE, 237. doi:10.1016/j.chemosphere.2019.124421

Gonyar, L. A., Gelbach, P. E., McDuffie, D. G., Koeppel, A. F., Chen, Q., Lee, G., . . . Eby, J. C. (2019). In Vivo Gene Essentiality and Metabolism in Bordetella pertussis. MSPHERE, 4(3). doi:10.1128/mSphere.00694-18

Papin, J. A., & Mac Gabhann, F. (2019). Wisdom of crowds in computational biology. PLOS COMPUTATIONAL BIOLOGY, 15(5). doi:10.1371/journal.pcbi.1007032

Untaroiu, A. M., Carey, M. A., Guler, J. L., & Papin, J. A. (2019). Leveraging the effects of chloroquine on resistant malaria parasites for combination therapies. BMC BIOINFORMATICS, 20. doi:10.1186/s12859-019-2756-y

Pannala, V. R., Vinnakota, K. C., Rawl, K. D., Estes, S. K., O'Brien, T. P., Printz, R. L., . . . Wallqvist, A. (2019). Mechanistic identification of biofluid metabolite changes as markers of acetaminophen-induced liver toxicity in rats. TOXICOLOGY AND APPLIED PHARMACOLOGY, 372, 19-32. doi:10.1016/j.taap.2019.04.001

Blazier, A. S., & Papin, J. A. (2019). Reconciling high-throughput gene essentiality data with metabolic network reconstructions. PLOS COMPUTATIONAL BIOLOGY, 15(4). doi:10.1371/journal.pcbi.1006507

Dunphy, L. J., Yen, P., & Papin, J. A. (2019). Integrated Experimental and Computational Analyses Reveal Differential Metabolic Functionality in Antibiotic-Resistant Pseudomonas aeruginosa. CELL SYSTEMS, 8(1), 3-+. doi:10.1016/j.cels.2018.12.002

Medlock, G., & Papin, J. (2019). Medusa: software to build and analyze ensembles of genome-scale metabolic network reconstructions. doi:10.1101/547174

Pradhan, D., Papin, J., & Jensen, P. (2019). Efficient enzyme coupling algorithms identify functional pathways in genome-scale metabolic models. doi:10.1101/608430

Jenior, M., Moutinho, T., Dougherty, B., & Papin, J. (2019). Transcriptome-guided parsimonious flux analysis improves predictions with metabolic networks in complex environments. doi:10.1101/637124

Carey, M., Dräger, A., Papin, J., & Yurkovich, J. (2019). Community standards to facilitate development and address challenges in metabolic modeling. doi:10.1101/700112

Moutinho, T., Neubert, B., Jenior, M., Carey, M., Medlock, G., Kolling, G., & Papin, J. (2019). Functional Anabolic Network Analysis of Human-associatedLactobacillusStrains. doi:10.1101/746420

Liu, Y., McGrath, J. S., Moore, J. H., Kolling, G. L., Papin, J. A., & Swami, N. S. (2019). Electrofabricated biomaterial-based capacitor on nanoporous gold for enhanced redox amplification. ELECTROCHIMICA ACTA, 318, 828-836. doi:10.1016/j.electacta.2019.06.127

Rawls, K. D., Dougherty, B. V., Blais, E. M., Stancliffe, E., Kolling, G. L., Vinnakota, K., . . . Papin, J. A. (2019). A simplified metabolic network reconstruction to promote understanding and development of flux balance analysis tools. COMPUTERS IN BIOLOGY AND MEDICINE, 105, 64-71. doi:10.1016/j.compbiomed.2018.12.010

Bourne, P. E., Lewitter, F., Markel, S., & Papin, J. A. (2018). One thousand simple rules. PLOS COMPUTATIONAL BIOLOGY, 14(12). doi:10.1371/journal.pcbi.1006670

Medlock, G. L., Carey, M. A., McDuffie, D. G., Mundy, M. B., Giallourou, N., Swann, J. R., . . . Papin, J. A. (2018). Inferring Metabolic Mechanisms of Interaction within a Defined Gut Microbiota. CELL SYSTEMS, 7(3), 245-+. doi:10.1016/j.cels.2018.08.003

Luzader, D., Moutinho, T. J., Mitchell, P., Papin, J., Hong, C., & Moore, S. (2018). 274 - Gut Microbial Metabolites Modulate the Amplitude and Phase of PER2 and BMAL1 Circadian Rhythms in Intestinal Epithelial Cells and Organoids. Gastroenterology, 154(6), S-67. doi:10.1016/s0016-5085(18)30681-4

Carey, M. A., Covelli, V., Brown, A., Medlock, G. L., Haaren, M., Cooper, J. G., . . . Guler, J. L. (2018). Influential Parameters for the Analysis of Intracellular Parasite Metabolomics. MSPHERE, 3(2). doi:10.1128/mSphere.00097-18

Medlock, G., Carey, M., McDuffie, D., Mundy, M., Giallourou, N., Swann, J., . . . Papin, J. (2018). Metabolic mechanisms of interaction within a defined gut microbiota. doi:10.1101/250860

Dunphy, L., Yen, P., & Papin, J. (2018). Network analysis reveals differential metabolic functionality in antibiotic-resistantPseudomonas aeruginosa. doi:10.1101/303289

Blazier, A., & Papin, J. (2018). Reconciling high-throughput gene essentiality data with metabolic network reconstructions. doi:10.1101/415448

Medlock, G., & Papin, J. (2018). Guiding the Refinement of Biochemical Knowledgebases with Ensembles of Metabolic Networks and Machine Learning. doi:10.1101/460071

Carey, M. A., & Papin, J. A. (2018). Ten simple rules for biologists learning to program. PLOS COMPUTATIONAL BIOLOGY, 14(1). doi:10.1371/journal.pcbi.1005871

Dunphy, L. J., & Papin, J. A. (2018). Biomedical applications of genome-scale metabolic network reconstructions of human pathogens. CURRENT OPINION IN BIOTECHNOLOGY, 51, 70-79. doi:10.1016/j.copbio.2017.11.014

Nussinov, R., & Papin, J. A. (2017). How can computation advance microbiome research?. PLOS COMPUTATIONAL BIOLOGY, 13(9). doi:10.1371/journal.pcbi.1005547

Yen, P., & Papin, J. A. (2017). History of antibiotic adaptation influences microbial evolutionary dynamics during subsequent treatment. PLOS BIOLOGY, 15(8). doi:10.1371/journal.pbio.2001586

Carey, M. A., Papin, J. A., & Guler, J. L. (2017). Novel Plasmodium falciparum metabolic network reconstruction identifies shifts associated with clinical antimalarial resistance. BMC GENOMICS, 18. doi:10.1186/s12864-017-3905-1

Bartelt, L. A., Bolick, D. T., Mayneris-Perxachs, J., Kolling, G. L., Medlock, G. L., Zaenker, E. I., . . . Guerrant, R. L. (2017). Cross-modulation of pathogen-specific pathways enhances malnutrition during enteric co-infection with Giardia lamblia and enteroaggregative Escherichia coli. PLOS PATHOGENS, 13(7). doi:10.1371/journal.ppat.1006471

Bolick, D. T., Mayneris-Perxachs, J., Medlock, G. L., Kolling, G. L., Papin, J. A., Swann, J. R., & Guerrant, R. L. (2017). Increased Urinary Trimethylamine N-Oxide Following Cryptosporidium Infection and Protein Malnutrition Independent of Microbiome Effects. JOURNAL OF INFECTIOUS DISEASES, 216(1), 64-71. doi:10.1093/infdis/jix234

Bartell, J. A., Blazier, A. S., Yen, P., Thogersen, J. C., Jelsbak, L., Goldberg, J. B., & Papin, J. A. (2017). Reconstruction of the metabolic network of Pseudomonas aeruginosa to interrogate virulence factor synthesis. NATURE COMMUNICATIONS, 8. doi:10.1038/ncomms14631

Biggs, M. B., & Papin, J. A. (2017). Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA. PLOS COMPUTATIONAL BIOLOGY, 13(3). doi:10.1371/journal.pcbi.1005413

Blais, E. M., Rawls, K. D., Dougherty, B. V., Li, Z. I., Kolling, G. L., Ye, P., . . . Papin, J. A. (2017). Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions. NATURE COMMUNICATIONS, 8. doi:10.1038/ncomms14250

Moutinho, T., Panagides, J., Biggs, M., Medlock, G., Kolling, G., & Papin, J. (2017). Novel co-culture plate enables growth dynamic-based assessment of contact-independent microbial interactions. doi:10.1101/145615

Carey, M., Covelli, V., Brown, A., Medlock, G., Haaren, M., Cooper, J., . . . Guler, J. (2017). Influential parameters for the analysis of intracellular parasite metabolomics. doi:10.1101/190421

Moutinho, T. J. J., Panagides, J. C., Biggs, M. B., Medlock, G. L., Kolling, G. L., & Papin, J. A. (2017). Novel co-culture plate enables growth dynamic-based assessment of contact-independent microbial interactions. PLOS ONE, 12(8). doi:10.1371/journal.pone.0182163

Janes, K. A., Chandran, P. L., Ford, R. M., Lazzara, M. J., Papin, J. A., Peirce, S. M., . . . Lauffenburger, D. A. (2017). An engineering design approach to systems biology. INTEGRATIVE BIOLOGY, 9(7), 574-583. doi:10.1039/c7ib00014f

Liu, A., Archer, A. M., Biggs, M. B., & Papin, J. A. (2017). Growth-altering microbial interactions are responsive to chemical context. PLOS ONE, 12(3). doi:10.1371/journal.pone.0164919

Nussinov, R., Papin, J. A., & Vakser, I. (2017). Computing the Dynamic Supramolecular Structural Proteome. PLOS COMPUTATIONAL BIOLOGY, 13(1). doi:10.1371/journal.pcbi.1005290

Biggs, M. B., Medlock, G. L., Moutinho, T. J., Lees, H. J., Swann, J. R., Kolling, G. L., & Papin, J. A. (2017). Systems-level metabolism of the altered Schaedler flora, a complete gut microbiota. ISME JOURNAL, 11(2), 426-438. doi:10.1038/ismej.2016.130

Mayneris-Perxachs, J., Bolick, D. T., Leng, J., Medlock, G. L., Kolling, G. L., Papin, J. A., . . . Guerrant, R. L. (2016). Protein- and zinc-deficient diets modulate the murine microbiome and metabolic phenotype. AMERICAN JOURNAL OF CLINICAL NUTRITION, 104(5), 1253-1262. doi:10.3945/ajcn.116.131797

Nussinov, R., & Papin, J. A. (2016). Computing Biology. PLOS COMPUTATIONAL BIOLOGY, 12(7). doi:10.1371/journal.pcbi.1005050

Liu, A., Archer, A., Biggs, M., & Papin, J. (2016). Growth-Altering Microbial Interactions Are Highly Sensitive to Environmental Context. doi:10.1101/079251

Biggs, M., & Papin, J. (2016). Managing Uncertainty in Metabolic Network Structure and Improving Predictions Using EnsembleFBA. doi:10.1101/077636

Yen, P., & Papin, J. (2016). History of Antibiotic Adaptation Influences Microbial Evolutionary Dynamics During Subsequent Treatment. doi:10.1101/089334

Chaiboonchoe, A., Ghamsari, L., Dohai, B., Ng, P., Khraiwesh, B., Jaiswal, A., . . . Salehi-Ashtiani, K. (2016). Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation. MOLECULAR BIOSYSTEMS, 12(8), 2394-2407. doi:10.1039/c6mb00237d

Biggs, M. B., & Papin, J. A. (2016). Metabolic network-guided binning of metagenomic sequence fragments. BIOINFORMATICS, 32(6), 867-874. doi:10.1093/bioinformatics/btv671

Varga, J. J., Barbier, M., Mulet, X., Bielecki, P., Bartell, J. A., Owings, J. P., . . . Goldberg, J. B. (2015). Genotypic and phenotypic analyses of a Pseudomonas aeruginosa chronic bronchiectasis isolate reveal differences from cystic fibrosis and laboratory strains. BMC GENOMICS, 16. doi:10.1186/s12864-015-2069-0

Ebrahim, A., Almaas, E., Bauer, E., Bordbar, A., Burgard, A. P., Chang, R. L., . . . Thiele, I. (2015). Do genome-scale models need exact solvers or clearer standards?. MOLECULAR SYSTEMS BIOLOGY, 11(10). doi:10.15252/msb.20156157

Nussinov, R., Bonhoeffer, S., Papin, J. A., & Sporns, O. (2015). From "What Is?" to "What Isn't?" Computational Biology. PLOS COMPUTATIONAL BIOLOGY, 11(7). doi:10.1371/journal.pcbi.1004318

Steinway, S. N., Biggs, M. B., Loughran, T. P. J., Papin, J. A., & Albert, R. (2015). Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome. PLOS COMPUTATIONAL BIOLOGY, 11(6). doi:10.1371/journal.pcbi.1004338

D'Auria, K. M., Bloom, M. J., Reyes, Y., Gray, M. C., Van Opstal, E. J., Papin, J. A., & Hewlett, E. L. (2015). High temporal resolution of glucosyltransferase dependent and independent effects of Clostridium difficile toxins across multiple cell types. BMC MICROBIOLOGY, 15. doi:10.1186/s12866-015-0361-4

Biggs, M. B., Medlock, G. L., Kolling, G. L., & Papin, J. A. (2015). Metabolic network modeling of microbial communities. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE, 7(5), 317-334. doi:10.1002/wsbm.1308

Jensen, P. A., Dougherty, B. V., Moutinho, T. J. J., & Papin, J. A. (2015). Miniaturized Plate Readers for Low-Cost, High-Throughput Phenotypic Screening. JALA, 20(1), 51-55. doi:10.1177/2211068214555414

Jensen, P. A., & Papin, J. A. (2014). MetDraw: automated visualization of genome-scale metabolic network reconstructions and high-throughput data. BIOINFORMATICS, 30(9), 1327-1328. doi:10.1093/bioinformatics/btt758

Newhook, T. E., Blais, E. M., Lindberg, J. M., Adair, S. J., Xin, W., Lee, J. K., . . . Bauer, T. W. (2014). A Thirteen-Gene Expression Signature Predicts Survival of Patients with Pancreatic Cancer and Identifies New Genes of Interest. PLOS ONE, 9(9). doi:10.1371/journal.pone.0105631

Bartell, J. A., Yen, P., Varga, J. J., Goldberg, J. B., & Papin, J. A. (2014). Comparative Metabolic Systems Analysis of Pathogenic Burkholderia. JOURNAL OF BACTERIOLOGY, 196(2), 210-226. doi:10.1128/JB.00997-13

Wagenseller, A. G., Shada, A. L., D'Auria, K., Murphy, C. F., Sun, D., Molhoek, K. R., . . . Slingluff, C. L. (2012). MicroRNAs induced in melanoma treated with combination targeted therapy of temsirolimus and bevacizumab. JOURNAL OF CLINICAL ONCOLOGY, 30(15). Retrieved from https://www.webofscience.com/

Koskimaki, J. E., Blazier, A. S., Clarens, A. F., & Papin, J. A. (2013). Computational Models of Algae Metabolism for Industrial Applications. Industrial Biotechnology, 9(4), 185-195. doi:10.1089/ind.2013.0012

D'Auria, K. M., Kolling, G. L., Donato, G. M., Warren, C. A., Gray, M. C., Hewlett, E. L., & Papin, J. A. (2013). In Vivo Physiological and Transcriptional Profiling Reveals Host Responses to Clostridium difficile Toxin A and Toxin B. INFECTION AND IMMUNITY, 81(10), 3814-3824. doi:10.1128/IAI.00869-13

Thiele, I., Swainston, N., Fleming, R. M. T., Hoppe, A., Sahoo, S., Aurich, M. K., . . . Palsson, B. O. (2013). A community-driven global reconstruction of human metabolism. NATURE BIOTECHNOLOGY, 31(5), 419-+. doi:10.1038/nbt.2488

Blais, E. M., Chavali, A. K., & Papin, J. A. (2013). Linking genome-scale metabolic modeling and genome annotation.. Methods in molecular biology (Clifton, N.J.), 985, 61-83. doi:10.1007/978-1-62703-299-5_4

Biggs, M. B., & Papin, J. A. (2013). Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation. PLOS ONE, 8(10). doi:10.1371/journal.pone.0078011

Walpole, J., Papin, J. A., & Peirce, S. M. (2013). Multiscale Computational Models of Complex Biological Systems. ANNUAL REVIEW OF BIOMEDICAL ENGINEERING, VOL 15, 15, 137-154. doi:10.1146/annurev-bioeng-071811-150104

Walters, D. M., Stokes, J. B., Adair, S. J., Stelow, E. B., Borgman, C. A., Lowrey, B. T., . . . Bauer, T. W. (2013). Clinical, Molecular and Genetic Validation of a Murine Orthotopic Xenograft Model of Pancreatic Adenocarcinoma Using Fresh Human Specimens. PLOS ONE, 8(10). doi:10.1371/journal.pone.0077065

Schmidt, B. J., Papin, J. A., & Musante, C. J. (2013). Mechanistic systems modeling to guide drug discovery and development. DRUG DISCOVERY TODAY, 18(3-4), 116-127. doi:10.1016/j.drudis.2012.09.003

Chavali, A. K., Blazier, A. S., Tlaxca, J. L., Jensen, P. A., Pearson, R. D., & Papin, J. A. (2012). Metabolic network analysis predicts efficacy of FDA-approved drugs targeting the causative agent of a neglected tropical disease. BMC SYSTEMS BIOLOGY, 6. doi:10.1186/1752-0509-6-27

Chavali, A. K., D'Auria, K. M., Hewlett, E. L., Pearson, R. D., & Papin, J. A. (2012). A metabolic network approach for the identification and prioritization of antimicrobial drug targets. TRENDS IN MICROBIOLOGY, 20(3), 113-123. doi:10.1016/j.tim.2011.12.004

D'Auria, K. M., Donato, G. M., Gray, M. C., Kolling, G. L., Warren, C. A., Cave, L. M., . . . Hewlett, E. L. (2012). Systems analysis of the transcriptional response of human ileocecal epithelial cells to Clostridium difficile toxins and effects on cell cycle control. BMC SYSTEMS BIOLOGY, 6. doi:10.1186/1752-0509-6-2

Blazier, A. S., & Papin, J. A. (2012). Integration of expression data in genome-scale metabolic network reconstructions. FRONTIERS IN PHYSIOLOGY, 3. doi:10.3389/fphys.2012.00299

Tilghman, R. W., Blais, E. M., Cowan, C. R., Sherman, N. E., Grigera, P. R., Jeffery, E. D., . . . Parsons, J. T. (2012). Matrix Rigidity Regulates Cancer Cell Growth by Modulating Cellular Metabolism and Protein Synthesis. PLOS ONE, 7(5). doi:10.1371/journal.pone.0037231

Jensen, P. A., Lutz, K. A., & Papin, J. A. (2011). TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks. BMC SYSTEMS BIOLOGY, 5. doi:10.1186/1752-0509-5-147

Chang, R. L., Ghamsari, L., Manichaikul, A., Hom, E. F. Y., Balaji, S., Fu, W., . . . Papin, J. A. (2011). Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism. MOLECULAR SYSTEMS BIOLOGY, 7. doi:10.1038/msb.2011.52

Molhoek, K. R., Shada, A. L., Smolkin, M., Chowbina, S., Papin, J., Brautigan, D. L., & Slingluff, C. L. J. (2011). Comprehensive analysis of receptor tyrosine kinase activation in human melanomas reveals autocrine signaling through IGF-1R. MELANOMA RESEARCH, 21(4), 274-284. doi:10.1097/CMR.0b013e328343a1d6

Ghamsari, L., Balaji, S., Shen, Y., Yang, X., Balcha, D., Fan, C., . . . Salehi-Ashtiani, K. (2011). Genome-wide functional annotation and structural verification of metabolic ORFeome of Chlamydomonas reinhardtii. BMC GENOMICS, 12. doi:10.1186/1471-2164-12-S1-S4

Oberhardt, M. A., Puchalka, J., dos Santos, V. A. P. M., & Papin, J. A. (2011). Reconciliation of Genome-Scale Metabolic Reconstructions for Comparative Systems Analysis. PLOS COMPUTATIONAL BIOLOGY, 7(3). doi:10.1371/journal.pcbi.1001116

Haggart, C. R., Bartell, J. A., Saucerman, J. J., & Papin, J. A. (2011). WHOLE-GENOME METABOLIC NETWORK RECONSTRUCTION AND CONSTRAINT-BASED MODELING. METHODS IN ENZYMOLOGY, VOL 500, 500, 411-433. doi:10.1016/B978-0-12-385118-5.00021-9

Jensen, P. A., & Papin, J. A. (2011). Functional integration of a metabolic network model and expression data without arbitrary thresholding. BIOINFORMATICS, 27(4), 541-547. doi:10.1093/bioinformatics/btq702

Benedict, K. F., Mac Gabhann, F., Amanfu, R. K., Chavali, A. K., Gianchandani, E. P., Glaw, L. S., . . . Skalak, T. C. (2011). Systems Analysis of Small Signaling Modules Relevant to Eight Human Diseases. ANNALS OF BIOMEDICAL ENGINEERING, 39(2), 621-635. doi:10.1007/s10439-010-0208-y

Oberhardt, M. A., Goldberg, J. B., Hogardt, M., & Papin, J. A. (2010). Metabolic Network Analysis of Pseudomonas aeruginosa during Chronic Cystic Fibrosis Lung Infection. JOURNAL OF BACTERIOLOGY, 192(20), 5534-5548. doi:10.1128/JB.00900-10

Ruppin, E., Papin, J. A., de Figueiredo, L. F., & Schuster, S. (2010). Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks. CURRENT OPINION IN BIOTECHNOLOGY, 21(4), 502-510. doi:10.1016/j.copbio.2010.07.002

Schmidt, B. J., Lin-Schmidt, X., Chamberlin, A., Salehi-Ashtiani, K., & Papin, J. A. (2010). Metabolic systems analysis to advance algal biotechnology. BIOTECHNOLOGY JOURNAL, 5(7), 660-670. doi:10.1002/biot.201000129

Sefcik, L. S., Wilson, J. L., Papin, J. A., & Botchwey, E. A. (2010). Harnessing Systems Biology Approaches to Engineer Functional Microvascular Networks. TISSUE ENGINEERING PART B-REVIEWS, 16(3), 361-370. doi:10.1089/ten.teb.2009.0611

Glass, G., Papin, J. A., & Mandell, J. W. (2010). SIMPLE: A Sequential Immunoperoxidase Labeling and Erasing Method (vol 57, pg 899, 2009). JOURNAL OF HISTOCHEMISTRY & CYTOCHEMISTRY, 58(10), 939. doi:10.1369/jhc.2010.957209

Gianchandani, E. P., Chavali, A. K., & Papin, J. A. (2010). The application of flux balance analysis in systems biology. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE, 2(3), 372-382. doi:10.1002/wsbm.60