Viral Pandemics Group Publications Page

Publications From the Viral Pandemics Group and Group Members

  1. Arsène S, Couty C, Faddeenkov I, Go N, Granjeon-Noriot S, Šmít D, Kahoul R, Illigens B, Boissel JP, Chevalier A, Lehr L, Pasquali C, Kulesza A. Modeling the disruption of respiratory disease clinical trials by non-pharmaceutical COVID-19 interventions. Nat Commun. 2022 Apr 13;13(1):1980. doi: 10.1038/s41467-022-29534-8. PMID: 35418135; PMCID: PMC9008035.

  2. Aponte-Serrano JO, Weaver JJA, Sego TJ, Glazier JA, Shoemaker JE. Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics. PLoS Comput Biol. 2021 Oct 25;17(10):e1008874. doi: 10.1371/journal.pcbi.1008874. PMID: 34695114; PMCID: PMC8608315.

  3. Amidei A, Dobrovolny HM. Estimation of virus-mediated cell fusion rate of SARS-CoV-2. Virology. 2022 Oct;575:91-100. doi: 10.1016/j.virol.2022.08.016. Epub 2022 Sep 7. PMID: 36088794; PMCID: PMC9449781.

  4. Mochan E, Sego TJ, Gaona L, Rial E, Ermentrout GB. Compartmental Model Suggests Importance of Innate Immune Response to COVID-19 Infection in Rhesus Macaques. Bull Math Biol. 2021 May 26;83(7):79. doi: 10.1007/s11538-021-00909-0. PMID: 34037874; PMCID: PMC8149925.

  5. Zhang T, Androulakis IP, Bonate P, Cheng L, Helikar T, Parikh J, Rackauckas C, Subramanian K, Cho CR; Working Group. Two heads are better than one: current landscape of integrating QSP and machine learning : An ISoP QSP SIG white paper by the working group on the integration of quantitative systems pharmacology and machine learning. J Pharmacokinet Pharmacodyn. 2022 Feb;49(1):5-18. doi: 10.1007/s10928-022-09805-z. Epub 2022 Feb 1. PMID: 35103884; PMCID: PMC8837505.

  6. Mochan E, Sego TJ, and Bard Ermentrout B. Age-Related Changes to the Immune System Exacerbate the Inflammatory Response to Pandemic H1N1 Infection. Bulletin of mathematical biology 84, no. 8 (2022): 1-24.

  7. Cockrell C, Laria D, An G. Preparing for the next pandemic: Simulation-based deep reinforcementlearning to discover and test multimodal control of systemic inflammation using repurposed immunomodulatory agents. Front. Immunol., 21 Nov. 2022 Sec. Systems Immunology

  8. Chesnais F, Hue J, Roy E, Branco M, Stokes R, Pellon A, Le Caillec J, Elbahtety E, Battilocchi M, Danovi D, Veschini L. High-content image analysis to study phenotypic heterogeneity in endothelial cell monolayers. J Cell Sci. 2022 Jan 15;135(2):jcs259104. doi: 10.1242/jcs.259104. Epub 2022 Jan 26.
  9. Chesnais F,  Sego TJ, Engstler E, Battilocchi M, Danovi D, Glazier JA, Veschini L. A spatialised agent-based model of NOTCH signalling pathway in Endothelial Cells predicts emergent heterogeneity due to continual dynamic phenotypic adjustments. bioRxiv 2022.08.06.503043; doi:

  10. Hue J, Valinciute Z, Thavaraj S, Veschini L. High content image analysis in routine diagnostic histopathology predicts outcomes in HPV-associated oropharyngeal squamous cell carcinomas. medRxiv 2022.06.24.22276368; doi:

  11. Kuhl, Ellen (2021). Book: Computational Epidemiology: Data-Driven Modeling of COVID-19, Springer Nature. doi:10.1007/978-3-030-82890-5, ISBN 978-3-030-82889-9, S2CID 237588620.

  12. Böttcher L, Antulov-Fantulin N, Asikis T. AI Pontryagin or how artificial neural networks learn to control dynamical systems. Nat Commun. 2022 Jan 17;13(1):333. doi: 10.1038/s41467-021-27590-0. PMID: 35039488; PMCID: PMC8763915.
  13. Böttcher L, and Asikis T. Near-optimal control of dynamical systems with neural ordinary differential equations. Machine Learning: Science and Technology. Accepted 16 September 2022. Available online here.
  14. Waites W, Cavaliere M, Danos V, Datta R, Eggo RM, Hallett TB, Manheim D, Panovska-Griffiths J, Russell TW, Zarnitsyna VI. Compositional modelling of immune response and virus transmission dynamics. Philos Trans A Math Phys Eng Sci. 2022 Oct 3;380(2233):20210307. doi: 10.1098/rsta.2021.0307. Epub 2022 Aug 15. PMID: 35965463.
  15. An G and Cockrell C. Drug Development Digital Twins for Drug Discovery, Testing and Repurposing: A Schema for Requirements and Development. Front. Syst. Biol., 20 June 2022, Sec. Translational Systems Biology and In Silico Trials
  16. Darquenne, C. Borojeni, A.A.T. Colebank, M.J.Forest, M.G. Madas, B.G. Tawhai M.and Jiang, Y. Aerosol transport modeling: the key link between lung infections of individuals and populations. Frontiers Physiol., 13:923945, 2022
    (publication from the VP WG Lung, Pulmonary, Circulation and Aerosol Transport Subgroup)
  17. Laubenbacher R, Niarakis A, Helikar T, An G, Shapiro B, Malik-Sheriff RS, Sego TJ, Knapp A, Macklin P, Glazier JA. Building digital twins of the human immune system: toward a roadmap. NPJ Digit Med. 2022 May 20;5(1):64. doi: 10.1038/s41746-022-00610-z. PMID: 35595830; PMCID: PMC9122990.

  18. JM Sasso, BJB Ambrose, R Tenchov, RS Datta, MT Basel, RK DeLong, QA Zhou. The Progress and Promise of RNA Medicine─An Arsenal of Targeted Treatments. J Med Chem. 2022 May 9. doi: 10.1021/acs.jmedchem.2c00024. Epub ahead of print. PMID: 35533054.

  19. Fain, B, and H.M. Dobrovolny, GPU acceleration and data fitting: Agent-based models of viral infections can now be parameterized in hours, Journal of Computational Science,

  20. Dale Larie, Gary An, Robert Chase Cockrell, Preparing for the next COVID: Deep Reinforcement Learning trained Artificial Intelligence discovery of multi-modal immunomodulatory control of systemic inflammation in the absence of effective anti-microbials
  21. Gary An, Specialty Grand Challenge: What it will take to cross the Valley of Death: Translational Systems Biology, “True” Precision Medicine, Medical Digital Twins, Artificial Intelligence and In Silico Clinical trials (Provisionally accepted, pending final quality checks)
  22. Pinky, L., and H.M, Dobrovolny, Epidemiological consequences of viral interference: A mathematical modeling study of two interacting viruses, Frontiers in Microbiology 13:822606, March 2022,
  23. Rita M C de Almeida, Gilberto L Thomas, James A Glazier, Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection, NAR Genomics and Bioinformatics, Volume 4, Issue 1, March 2022, lqac020,
  24. Karr J, Malik-Sheriff RS, Osborne J, Gonzalez-Parra G, Forgoston E, Bowness R, Liu Y, Thompson R, Garira W, Barhak J, Rice J, Torres M, Dobrovolny HM, Tang T, Waites W, Glazier JA, Faeder JR and Kulesza A (2022) Model Integration in Computational Biology: The Role of Reproducibility, Credibility and Utility. Front. Syst. Biol. 2:822606. doi: 10.3389/fsysb.2022.822606
  25. Ferrari Gianlupi, J.; Mapder, T.; Sego, T.J.; Sluka, J.P.; Quinney, S.K.; Craig, M.; Stratford, R.E., Jr.; Glazier, J.A. "Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2". Viruses 2022, 14, 605.
  26. Sego TJ, Mochan ED, Ermentrout GB, Glazier JA. "A multiscale multicellular spatiotemporal model of local influenza infection and immune response." J Theor Biol. 2021 Sep 27;532:110918. doi: 10.1016/j.jtbi.2021.110918. Epub ahead of print. PMID: 34592264; PMCID: PMC8478073.
  27. Sego TJ, Aponte-Serrano JO, Gianlupi JF, Glazier JA. "Generation of multicellular spatiotemporal models of population dynamics from ordinary differential equations, with applications in viral infection". BMC Biol. 2021 Sep 8;19(1):196. PMID: 34496857.
  28. Veronika I Zarnitsyna, Juliano Ferrari Gianlupi, Amit Hagar, TJ Sego, James A Glazier. "Advancing therapies for viral infections using mechanistic computational models of the dynamic interplay between the virus and host immune response." Current Opinion in Virology, 50, October 2021, Pages 103-109.
  29. Cockrell, C.; An, G. "Comparative Computational Modeling of the Bat and Human Immune Response to Viral Infection with the Comparative BiologyImmune Agent Based Model." Viruses 2021, 13, 1620.
  30. Sarah M Bartsch, Patrick T Wedlock, Kelly J O’Shea, Sarah N Cox, Ulrich Strych, Jennifer B Nuzzo, Marie C Ferguson, Maria Elena Bottazzi, Sheryl S Siegmund, Peter J Hotez, Bruce Y Lee, Lives and Costs Saved by Expanding and Expediting Coronavirus Disease 2019 Vaccination, The Journal of Infectious Diseases, Volume 224, Issue 6, 15 September 2021, Pages 938–948,
  31. Laubenbacher R, Sluka JP, Glazier JA. Using digital twins in viral infection. Science. 2021 Mar 12;371(6534):1105-1106. doi: 10.1126/science.abf3370. PMID: 33707255.
  32. Masison, J., J. Beezley, Y. Mei, H. a. L. Ribeiro, A. C. Knapp, L. Sordo Vieira, B. Adhikari,  Y. Scindia, M. Grauer, B. Helba,W. Schroeder, B. Mehrad,  R. Laubenbacher. A Modular Computational Framework for Medical Digital Twins. Proceedings of the National Academy of Sciences 118, no. 20 (May 18, 2021).
  33. Sego TJ, Aponte-Serrano JO, Ferrari Gianlupi J, Heaps SR, Breithaupt K, Brusch L, Osborne JM, Quardokus EM, Plemper RK, Glazier JA. A modular framework for multiscale, multicellular, spatiotemporal modeling of acute primary viral infection and immune response in epithelial tissues and its application to drug therapy timing and effectiveness, bioRxiv 2020.04.27.064139; doi:
  34. Getz M, Wang Y, An G, Becker A, Cockrell C, Collier N, Craig M, Davis CL, Faeder J, Ford Versypt AN, Ferrari Gianlupi J, Glazier JA, Hamis S, Heiland R, Hillen T, Hou D, Aminul Islam M, Jenner A, Kurtoglu F, Liu B, Macfarlane F, Maygrundter P, Morel PA, Narayanan A, Ozik J, Pienaar E, Rangamani P, Shoemaker JE, Smith AM, Macklin P. Rapid community-driven development of a SARS-CoV-2 tissue simulator, bioRxiv 2020.04.02.019075; doi:
  35. Jessie B, Dobrovolny HM, The role of syncytia during viral infections, 2021, Journal of Theoretical Biology, 525:110749, doi:10.1016/j.jtbi.2021.110749
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