{
	"event_id": "1111099",
	"eventinstance_id": "4116769",
	"calendar": {
		"id": 5827,
		"title": "Test",
		"slug": "test",
		"url": "https://events.ucf.edu/calendar/5827/test/"
	},
	"id": "4116769",
	"title": "Mathematical Biology Seminar by Dr. Denise Kirschner, University of Michigan Medical School",
	"subtitle": null,
	"description": "\u003Cp\u003EDr. \u003Ca href\u003D\u0022https://medschool.umich.edu/profile/4513/denise\u002De\u002Dkirschner\u0022 target\u003D\u0022_blank\u0022\u003E\u003Cstrong\u003EDenise Kirschner\u003C/strong\u003E\u003C/a\u003E\u003Cspan\u003E \u003C/span\u003E\u003Cspan\u003E(University of Michigan Medical School)\u0026nbsp\u003B\u003C/span\u003Ewill present \u0026ldquo\u003B\u003Cstrong\u003E\u003Cem\u003EParameter Estimation, Calibration, Uncertainty and Sensitivity in Multiscale Models\u003C/em\u003E\u003C/strong\u003E\u0026ldquo\u003B at this week\u0027s\u003Cspan\u003E\u0026nbsp\u003B\u003C/span\u003E\u003Ca href\u003D\u0022https://sciences.ucf.edu/mathbio/mathematical\u002Dbiology\u002Dseminar/\u0022 target\u003D\u0022_blank\u0022\u003EMathematical Biology Seminar\u003C/a\u003E.\u003C/p\u003E\u000A\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C/strong\u003E\u003Cspan\u003E Mathematical and computational models of biological systems are increasingly complex, typically comprised of hybrid multi\u002Dscale methods such as ordinary differential equations, partial differential equations, agent\u002Dbased and rule\u002Dbased models, etc. These mechanistic, multiscale models concurrently simulate detail at resolutions of whole host, multi\u002Dorgan, organ, tissue, cellular, molecular, and genomic dynamics. Lacking analytical and numerical methods, solving complex biological models requires iterative parameter sampling\u002Dbased approaches to establish appropriate ranges, of model parameters that capture corresponding experimental datasets. However, these models typically comprise large numbers of parameters and therefore large degrees of freedom. Thus, fitting these models to multiple experimental datasets over time and space presents significant challenges. We undertake the task of advancing calibration practices across models and dataset types for model calibration. Evaluating the process of calibrating models includes weighing strengths and applicability of each approach as well as standardizing calibration methods. We compare the performance of our model agnostic Calibration Protocol (CaliPro) with approximate Bayesian computing (ABC) to highlight strengths, weaknesses, synergies, and differences among these methods. Due to the typically nonlinear and stochastic nature of multiscale models as well as unknown parameter values, various types of uncertainty are present\u003B thus, effective assessment and quantification of such uncertainty through sensitivity analysis is important. We present ideas for global sensitivity analysis in the context of multiscale and multi\u002Dcompartment models and highlight its value in model development and analysis. We present an overview of sensitivity analysis methods, approaches for extending such methods to a multiscale setting, and examples of how sensitivity analysis can inform model reduction. Through schematics and references to past work, we aim to emphasize the advantages and usefulness of such techniques.\u003C/span\u003E\u003C/p\u003E\u000A\u003Cp\u003E\u003Cstrong\u003EShort Bio:\u0026nbsp\u003B\u003C/strong\u003EDr. Denise Kirschner is a full professor in the Department of Microbiology and Immunology at the University of Michigan Medical School. She received her Bachelors, Master\u0026rsquo\u003Bs and PhD in mathematical biology from Tulane University in Louisiana (USA).\u0026nbsp\u003B She did graduate work also at Los Alamos National Laboratory and a postdoctoral fellowship at Vanderbilt University joint in the division of Infectious Diseases. For the past 30 years, her research focus has been on describing the host immune response to \u003Cem\u003EM. tuberculosis\u003C/em\u003E during infection at multiple spatial and time scales and in multiple physiological sites including lung, lymph nodes and blood. She has worked and collaborated extensively with clinicians and experimentalists generating data on TB with non\u002Dhuman primate and clinical studies. A key recent focus of her work is identifying new regimens to treat TB.\u0026nbsp\u003B Dr. Kirschner has recently stepped down as Editor\u002Din\u002DChief of the \u003Cem\u003EJournal of Theoretical Biology\u003C/em\u003E after serving for 20 years. She serves as the founding co\u002Ddirector of The Center for Systems Biology at the University of Michigan Medical School, an interdisciplinary center at the University of Michigan aimed to facilitate research and training between wet\u002Dlab and theoretical scientists.\u0026nbsp\u003B She has been named a fellow of three societies: the American Association of Microbiologists, Society for Mathematical Biology and The Society for Industrial and Applied Mathematics.\u003C/p\u003E\u000A\u003Cp\u003E\u003Cspan\u003E\u003C/span\u003E\u003C/p\u003E",
	"location": "MSB 318: Mathematical Sciences Building, Room 318",
	"location_url": "https://www.ucf.edu/location/mathematical\u002Dsciences\u002Dbuilding/",
	"virtual_url": null,
	"registration_link": null,
	"registration_info": null,
	"starts": "Thu, 23 Apr 2026 09:30:00 -0400",
	"ends": "Thu, 23 Apr 2026 10:30:00 -0400",
	"ongoing": "False",
	"category": "Speaker/Lecture/Seminar",
	"tags": ["UCF Statistics","UCF Biology","UCF College of Medicine","UCF Mathematics"],
	"contact_name": "Zhisheng Shuai",
	"contact_phone": null,
	"contact_email": "Zhisheng.Shuai@ucf.edu",
	"url": "https://events.ucf.edu/event/4116769/mathematical-biology-seminar-by-dr-denise-kirschner-university-of-michigan-medical-school/"
}