Using PyBioNetFit to leverage qualitative and quantitative data in biological model parameterization and uncertainty quantification.
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| Title: | Using PyBioNetFit to leverage qualitative and quantitative data in biological model parameterization and uncertainty quantification. |
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| Authors: | Miller EF; Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States., Mallela A; Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, United States.; Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, United States., Neumann J; Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, United States., Lin YT; Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, United States.; Information Sciences Group, Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, United States., Hlavacek WS; Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, United States.; Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, United States., Posner RG; Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States. |
| Source: | Frontiers in immunology [Front Immunol] 2026 Apr 29; Vol. 17, pp. 1663008. Date of Electronic Publication: 2026 Apr 29 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101560960 Publication Model: eCollection Cited Medium: Internet ISSN: 1664-3224 (Electronic) Linking ISSN: 16643224 NLM ISO Abbreviation: Front Immunol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1664-3224 |
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| DOI: | 10.3389/fimmu.2026.1663008 |
