How bioinformatics can help reverse engineer human aging

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.