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Computational Biology: Modeling Chronic Renal Allograft Injury

By Mark D Stegall and Richard eBorrows

Abstract

New approaches are need to develop more effective interventions to prevent long-term rejection of organ allografts. Computational biology provides a powerful tool to assess the large amount of complex data that is generated in longitudinal studies in this area. This manuscript outlines how our two groups are using mathematical modeling to analyze predictors of graft loss using both clinical and experimental data and how we plan to expand this approach to investigate specific mechanisms of chronic renal allograft injury

Topics: Computational Biology, mathematical modeling, immunology, Renal transplantation, chronic renal allograft dysfunction, Immunologic diseases. Allergy, RC581-607
Publisher: Frontiers Media S.A.
Year: 2015
DOI identifier: 10.3389/fimmu.2015.00385
OAI identifier: oai:doaj.org/article:7f5262096d764e609285e881ec48c0d0
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