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A case for the reuse and adaptation of mechanistic computational models to study transplant immunology.
Fribourg, Miguel.
Afiliación
  • Fribourg M; Department of Medicine, and Immunology Institute, Icahn School of Medicine at Mount Sinai, Translational Transplant Research Center, New York, New York.
Am J Transplant ; 20(2): 355-361, 2020 02.
Article en En | MEDLINE | ID: mdl-31562790
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Simulación por Computador / Modelos Inmunológicos / Tolerancia al Trasplante / Rechazo de Injerto / Supervivencia de Injerto Límite: Humans Idioma: En Revista: Am J Transplant Asunto de la revista: TRANSPLANTE Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Simulación por Computador / Modelos Inmunológicos / Tolerancia al Trasplante / Rechazo de Injerto / Supervivencia de Injerto Límite: Humans Idioma: En Revista: Am J Transplant Asunto de la revista: TRANSPLANTE Año: 2020 Tipo del documento: Article