DEDiscover is a workflow-based differential equation modeling software tool for scientists, statisticians, and modelers. Whether you need to do quick simulation, develop sophisticated models, or teach mathematical concepts, DEDiscover combines a powerful computation engine with a user-friendly interface to give you a tool that’s better, faster, and easier-to-use. (Source:

References in zbMATH (referenced in 8 articles )

Showing results 1 to 8 of 8.
Sorted by year (citations)

  1. Yan, Ada W.C.; Cao, Pengxing; Heffernan, Jane M.; McVernon, Jodie; Quinn, Kylie M.; La Gruta, Nicole L.; Laurie, Karen L.; McCaw, James M.: Modelling cross-reactivity and memory in the cellular adaptive immune response to influenza infection in the host (2017)
  2. Eftimie, Raluca; Gillard, Joseph J.; Cantrell, Doreen A.: Mathematical models for immunology: current state of the art and future research directions (2016)
  3. Yan, Ada W.C.; Cao, Pengxing; McCaw, James M.: On the extinction probability in models of within-host infection: the role of latency and immunity (2016)
  4. Crauste, F.; Terry, E.; Le Mercier, I.; Mafille, J.; Djebali, S.; Andrieu, T.; Mercier, B.; Kaneko, G.; Arpin, C.; Marvel, J.; Gandrillon, O.: Predicting pathogen-specific CD8 T cell immune responses from a modeling approach (2015)
  5. Petrie, Stephen M.; Butler, Jeff; Barr, Ian G.; McVernon, Jodie; Hurt, Aeron C.; McCaw, James M.: Quantifying relative within-host replication fitness in influenza virus competition experiments (2015)
  6. Lee, Yeonok; Wu, Hulin: Mars approach for global sensitivity analysis of differential equation models with applications to dynamics of influenza infection (2012)
  7. Louzoun, Yoram; Ganusov, Vitaly V.: Evolution of viral life-cycle in response to cytotoxic T lymphocyte-mediated immunity (2012)
  8. Dobrovolny, Hana M.; Gieschke, Ronald; Davies, Brian E.; Jumbe, Nelson L.; Beauchemin, Catherine A.A.: Neuraminidase inhibitors for treatment of human and avian strain influenza: a comparative modeling study (2011)