Computational Biology: Modeling Chronic Renal Allograft Injury

New approaches are needed 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.

• Publication year

  2015

• Venue

  Frontiers in Immunology

• Publication date

  2015-08-03

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.3389/fimmu.2015.00385PMID 26284070PMCID 4522871
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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