A case for the reuse and adaptation of mechanistic computational models to study transplant immunology

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Abstract

Computational mechanistic models constitute powerful tools for summarizing our knowledge in quantitative terms, providing mechanistic understanding, and generating new hypotheses. The present review emphasizes the advantages of reusing publicly available computational models as a way to capitalize on existing knowledge, reduce the number of parameters that need to be adjusted to experimental data, and facilitate hypothesis generation. Finally, it includes a step-by-step example of the reuse and adaptation of an existing model of immune responses to tuberculosis, tumor growth, and blood pathogens, to study donor-specific antibody (DSA) responses. This review aims to illustrate the benefit of leveraging the currently available computational models in immunology to accelerate the study of alloimmune responses, and to encourage modelers to share their models to further advance our understanding of transplant immunology.

Original languageEnglish
Pages (from-to)355-361
Number of pages7
JournalAmerican Journal of Transplantation
Volume20
Issue number2
DOIs
StatePublished - 1 Feb 2020

Keywords

  • T cell biology
  • alloantibody
  • alloantigen
  • basic (laboratory) research/science
  • cellular biology
  • immune regulation
  • immunobiology
  • molecular biology
  • signaling/signaling pathways
  • translational research/science

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