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...

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Detalles Bibliográficos
Autores principales: Stegall, Mark D., Borrows, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Immunology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4522871/
https://www.ncbi.nlm.nih.gov/pubmed/26284070
http://dx.doi.org/10.3389/fimmu.2015.00385
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author Stegall, Mark D.
Borrows, Richard
author_facet Stegall, Mark D.
Borrows, Richard
author_sort Stegall, Mark D.
collection PubMed
description 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.
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spelling pubmed-45228712015-08-17 Computational Biology: Modeling Chronic Renal Allograft Injury Stegall, Mark D. Borrows, Richard Front Immunol Immunology 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. Frontiers Media S.A. 2015-08-03 /pmc/articles/PMC4522871/ /pubmed/26284070 http://dx.doi.org/10.3389/fimmu.2015.00385 Text en Copyright © 2015 Stegall and Borrows. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Stegall, Mark D.
Borrows, Richard
Computational Biology: Modeling Chronic Renal Allograft Injury
title Computational Biology: Modeling Chronic Renal Allograft Injury
title_full Computational Biology: Modeling Chronic Renal Allograft Injury
title_fullStr Computational Biology: Modeling Chronic Renal Allograft Injury
title_full_unstemmed Computational Biology: Modeling Chronic Renal Allograft Injury
title_short Computational Biology: Modeling Chronic Renal Allograft Injury
title_sort computational biology: modeling chronic renal allograft injury
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4522871/
https://www.ncbi.nlm.nih.gov/pubmed/26284070
http://dx.doi.org/10.3389/fimmu.2015.00385
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AT borrowsrichard computationalbiologymodelingchronicrenalallograftinjury

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