While we cannot offer a full description of either ageing, integrative systems biology, or comparative genomics, we provide herein a brief description of our scientific strategy in order for users to better use the resources available in the Human Ageing Genomic Resources.

We developed the Human Ageing Genomic Resources to help understand the genetic basis of human ageing. The basic principle behind our approach is that the genome regulates rate of ageing in mammals, including humans, to a large extent (Miller 1999; de Magalhaes 2003). Therefore, in theory, it is possible to study how the human genome regulates ageing and age-related deterioration through computational approaches. Understanding the evolution of ageing has been widely used in the past (Rose 1991). Having fully sequenced genomes allows researchers to study the evolution of ageing with unprecedented detail. Even though the nature of the human ageing process remains unclear (de Magalhaes 2005), it is undeniable that certain genes make humans age slower than other primates and about 30 times slower than mice and rats. Finding those genes has tremendous biomedical applications and is one of the reasons why we created the Human Ageing Genomic Resources.

The human genome is indecipherable by itself. To harness its information one powerful approach is comparative genomics (Ureta-Vidal et al. 2003). That is, we must compare the human genome to that of other organisms to understand which regions of the genome do what. To do so we created software tools. And we created a database of ageing in animals to study the evolution of ageing. Finally, we created GenAge, a database of genes related to ageing. Most researchers agree that ageing is a complex, multigenic process. GenAge, and its human dataset in particular, allows us to focus on the genes and pathways more likely to be involved in ageing and it allows us to study the interactions of the genes and how they give rise to the ageing phenotype.

In HAGR, we interpret what we know about ageing in model organisms in light of human biology. Using a system-level approach that incorporates data from multiple sources, we attempt to build a more coherent model of the genetic and molecular mechanisms of human ageing (de Magalhaes & Toussaint 2004). Defining a gene as related to human ageing is subjective. We used different criteria to define different pathways and advise researchers to look at our gene database, as described elsewhere. By building and constantly upgrading GenAge we aim to provide resources and directions for research in biogerontology.

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