How bioinformatics can help reverse engineer human aging

被引：15

作者：

de Magalhaes, JP ^{[1
]}

Toussaint, O ^{[1
]}

机构：

[1] Univ Namur, FUNDP, Dept Biol, URBC,Unit Cellular Biochem & Biol, B-5000 Namur, Belgium

来源：

AGEING RESEARCH REVIEWS | 2004年 / 3卷 / 02期

关键词：

aging; bioinformatics; computational biology; gerontology; systems biology;

D O I：

10.1016/j.arr.2003.08.006

中图分类号：

Q2 [细胞生物学];

学科分类号：

071009 ; 090102 ;

摘要：

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. (C) 2003 Elsevier Ireland Ltd. All rights reserved.

引用

页码：125 / 141

页数：17

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