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Computational biology for ageing

High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing d...

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Detalles Bibliográficos
Autores principales: Wieser, Daniela, Papatheodorou, Irene, Ziehm, Matthias, Thornton, Janet M.
Formato: Texto
Lenguaje:English
Publicado: The Royal Society 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001313/
https://www.ncbi.nlm.nih.gov/pubmed/21115530
http://dx.doi.org/10.1098/rstb.2010.0286
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author Wieser, Daniela
Papatheodorou, Irene
Ziehm, Matthias
Thornton, Janet M.
author_facet Wieser, Daniela
Papatheodorou, Irene
Ziehm, Matthias
Thornton, Janet M.
author_sort Wieser, Daniela
collection PubMed
description High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions.
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spelling pubmed-30013132011-01-12 Computational biology for ageing Wieser, Daniela Papatheodorou, Irene Ziehm, Matthias Thornton, Janet M. Philos Trans R Soc Lond B Biol Sci Articles High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions. The Royal Society 2011-01-12 /pmc/articles/PMC3001313/ /pubmed/21115530 http://dx.doi.org/10.1098/rstb.2010.0286 Text en This Journal is © 2011 The Royal Society http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Wieser, Daniela
Papatheodorou, Irene
Ziehm, Matthias
Thornton, Janet M.
Computational biology for ageing
title Computational biology for ageing
title_full Computational biology for ageing
title_fullStr Computational biology for ageing
title_full_unstemmed Computational biology for ageing
title_short Computational biology for ageing
title_sort computational biology for ageing
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001313/
https://www.ncbi.nlm.nih.gov/pubmed/21115530
http://dx.doi.org/10.1098/rstb.2010.0286
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