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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...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2011
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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. |
format | Text |
id | pubmed-3001313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
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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