Literature DB >> 15177050

How bioinformatics can help reverse engineer human aging.

João Pedro de Magalhães1, Olivier Toussaint.   

Abstract

To study human aging is an enormous challenge. The complexity of the aging phenotype and the near impossibility of studying aging directly in humans oblige researchers to resort to models and extrapolations. Computational approaches offer a powerful set of tools to study human aging. In one direction we have data-mining methods, from comparative genomics to DNA microarrays, to retrieve information in large amounts of data. Afterwards, tools from systems biology to reverse engineering algorithms allow researchers to integrate different types of information to increase our knowledge about human aging. Computer methodologies will play a crucial role to reconstruct the genetic network of human aging and the associated regulatory mechanisms. Copyright 2003 Elsevier Ireland Ltd.

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Year:  2004        PMID: 15177050     DOI: 10.1016/j.arr.2003.08.006

Source DB:  PubMed          Journal:  Ageing Res Rev        ISSN: 1568-1637            Impact factor:   10.895


  5 in total

1.  Brain Aging and Regeneration after Injuries: an Organismal approach.

Authors:  Ana-Maria Buga; Raluca Vintilescu; Oltin Tiberiu Pop; Aurel Popa-Wagner
Journal:  Aging Dis       Date:  2011-09-20       Impact factor: 6.745

2.  Meta-analysis of age-related gene expression profiles identifies common signatures of aging.

Authors:  João Pedro de Magalhães; João Curado; George M Church
Journal:  Bioinformatics       Date:  2009-02-02       Impact factor: 6.937

3.  Trajectories of physiological dysregulation predicts mortality and health outcomes in a consistent manner across three populations.

Authors:  Emmanuel Milot; V Morissette-Thomas; Qing Li; Linda P Fried; Luigi Ferrucci; Alan A Cohen
Journal:  Mech Ageing Dev       Date:  2014-10-20       Impact factor: 5.432

4.  HAGR: the Human Ageing Genomic Resources.

Authors:  João Pedro de Magalhães; Joana Costa; Olivier Toussaint
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

Review 5.  Complex systems dynamics in aging: new evidence, continuing questions.

Authors:  Alan A Cohen
Journal:  Biogerontology       Date:  2015-05-20       Impact factor: 4.277

  5 in total

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