José Nunes de Alencar Neto
Applying Bayesian reasoning to electrocardiogram interpretation
Journal of electrocardiology
mathematical modeling provides rigorous way quantify immunological processes discriminate alternative mechanisms driving specific biological phenomena typical mathematical models immunological phenomena developed modelers explain specific sets experimental data data collected experimental collaborators whether available data sufficient accurately estimate model parameters discriminate alternative models typically investigated previously collected data may sufficient guide development alternative models help estimating model parameters data often allow discriminate alternative models case study develop series power analyses determine optimal sample sizes allow accurate estimation model parameters discrimination alternative models describing clustering cd8 cells around plasmodium liver stages typical experiments mice infected intravenously plasmodium sporozoites invade hepatocytes liver cells activated cd8 cells transferred infected mice number cells found vicinity individual infected hepatocytes different times cell transfer counted using intravital microscopy previously developed series mathematical models aimed explain highly variable number cells per parasite one models densitydependent recruitment ddr model fitted data preliminary experiments better alternative models densityindependent exit die model show ability discriminate alternative models depends number parasites imaged analysis analysis formula see text parasites 2 4 8 h cell transfer allow 95 probability select correct model type data collected also impact following cell clustering around individual parasites time called longitudinal lt data allows precise less biased estimates parameters ddr model generated traditional way imaging individual parasites different liver areasmice crosssectional cs data however lt imaging comes cost need keep mice alive microscope hours may ethically unacceptable finally show number time points measurements taken also impacts precision estimation ddr model parameters particular measuring cell clustering one time point allow accurately estimating parameters ddr model using case study propose general framework mathematical modeling used guide experimental designs power analyses complex biological processes