1150 W. Medical Center Drive, 6730 MedSci II
Ann Arbor, MI 48109
Available to mentor
Dr. Kirschner is a professor in the department of Microbiology and Immunology at the University of Michigan. She received her Bachelors, Masters and PhD in applied mathematics from Tulane University. She did graduate work also at Los Alamos National Labs and a postdoctoral fellowship at Vanderbilt University joint with the departments of Mathematics and Infectious Diseases. For the past 25 years, her research focus has been on building multi-scale models to describe the host immune response to M. tuberculosis at multiple spatial and time scales and in multiple physiological sites including lung, lymph nodes and blood. To date she have worked and collaborated with experimentalists generating data on TB with mouse, non-human primate and human studies. Dr. Kirschner currently serves (and has for the past 20 years) as Editor-in-Chief of the Journal of Theoretical Biology. She serves as the founding co-director of The Center for Systems Biology at the University of Michigan, an interdisciplinary center at the University of Michigan aimed to facilitate research and training between wet-lab and theoretical scientists.
Denise Kirschner Home Page Kirschner Lab
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Postdoctoral FellowVanderbilt University Medical Center, Mathematical Modeling, 1994
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PhDTulane University, New Orleans, 1991
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MSTulane University, New Orleans, 1988
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BSTulane University, New Orleans, 1985
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Center MemberCenter for Computational Medicine and Bioinformatics
The work in my laboratory focuses mainly on questions related to host-pathogen interactions in infectious diseases. This means defining both the immune responses and the microbial characteristics that lead to infection and disease. In particular, our main focus is studying persistent infections - infections that the host is not able to clear. The persistent pathogens we focus on include both bacteria (e.g. Helicobacter pylori and Mycobacterium tuberculosis) and HIV-1. Such pathogens have evolved strategies to evade or circumvent the host-immune response and our goal is to understand the complex dynamic involved in host-pathogen interactions, together with how perturbations to this interaction (via treatment with chemotherapies or immunotherapies) can lead to prolonged or permanent health of the patient. Drug-resistance and the effects of treatment can be efficiently studied in this setting.
Currently, our research focus is on the role of the host response in pathogenesis at multiple spatial and time scales. The grants funding our work aim to examine the immune responses in the lymph nodes and lung also during TB infection. There are unique structures, granulomas, which are involved in the immune response to M. tuberculosis and we are developing methods to better understand their formation and function. This data could have a profound impact on our understanding the different disease trajectories seen in patients infected with persistent pathogens.
We apply a range of computational tools from deterministic mathematical models to more discrete stochastic ones such as Agent Based Models and PDEs to examine spatial questions as well. We are focused on not only building multi-scale models, as that is key to studying these more complex biological systems but using them to study large open-questions related to biomarker discovery, treatment and vaccine development and testing.
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Laubenbacher R, Adler F, An G, Castiglione F, Eubank S, Fonseca LL, Glazier J, Helikar T, Jett-Tilton M, Kirschner D, Macklin P, Mehrad B, Moore B, Pasour V, Shmulevich I, Smith A, Voigt I, Yankeelov TE, Ziemssen T. NPJ Syst Biol Appl, 2024 Feb 16; 10 (1): 19Journal ArticleForum on immune digital twins: a meeting report.
DOI:10.1038/s41540-024-00345-5 PMID: 38365857 -
Budak M, Via LE, Weiner DM, Barry CE, Nanda P, Michael G, Mdluli K, Kirschner D. CPT Pharmacometrics Syst Pharmacol, 2024 Apr; 13 (4): 673 - 685.Journal ArticleA systematic efficacy analysis of tuberculosis treatment with BPaL-containing regimens using a multiscale modeling approach.
DOI:10.1002/psp4.13117 PMID: 38404200 -
Nanda P, Budak M, Michael CT, Krupinsky K, Kirschner DE. 2024 Jan 1; Part F2950: Modeling and Simulation in Science, Engineering and Technology, 11 - 43.ChapterDevelopment and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations
DOI:10.1007/978-3-031-56794-0_2 -
Irfan B, Yaqoob A, Yasin I, Kirschner D. Infectious Diseases in Clinical Practice, 2024 Jan 1; 32 (1):Journal ArticleRamadan Fasting: Recommendations for Patients with Flulike or Abdominal Symptoms
DOI:10.1097/IPC.0000000000001321 -
Laubenbacher R, Adler F, An G, Castiglione F, Eubank S, Fonseca LL, Glazier J, Helikar T, Jett-Tilton M, Kirschner D, Macklin P, Mehrad B, Moore B, Pasour V, Shmulevich I, Smith A, Voigt I, Yankeelov TE, Ziemssen T. Front Digit Health, 2024 6: 1349595Journal ArticleToward mechanistic medical digital twins: some use cases in immunology.
DOI:10.3389/fdgth.2024.1349595 PMID: 38515550 -
Nanda P, Budak M, Michael CT, Krupinsky K, Kirschner DE. 2023 Nov 15;PreprintDevelopment and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations.
DOI:10.1101/2023.11.13.566861 PMID: 38014103 -
Janakiraman S, Engels S, Nanda P, Budak M, Greenstein T, Moraes MP, Aldridge BB, Kirschner DE. STAR Protoc, 2023 Sep 15; 4 (3): 102442Journal ArticleSemi-automated colony-forming unit counting for biosafety level 3 laboratories.
DOI:10.1016/j.xpro.2023.102442 PMID: 37549035 -
Budak M, Cicchese JM, Maiello P, Borish HJ, White AG, Chishti HB, Tomko J, Frye LJ, Fillmore D, Kracinovsky K, Sakal J, Scanga CA, Lin PL, Dartois V, Linderman JJ, Flynn JL, Kirschner DE. PLoS Comput Biol, 2023 Jun; 19 (6): e1010823Journal ArticleOptimizing tuberculosis treatment efficacy: Comparing the standard regimen with Moxifloxacin-containing regimens.
DOI:10.1371/journal.pcbi.1010823 PMID: 37319311