This month, PLoS Computational Biology and the International Society for Computational Biology begin a series of short, practical articles for students and active researchers who want to learn more about new areas of computational biology and are unsure where or how to start. The aim of each article in the “Getting Started in…” series is to introduce the essentials: define the area and what it is about, highlight the debates and issues of relevance, and provide directions to the most relevant books, articles, or Web sites to find out more.

Previous research showed that the frequency of deleterious genotype of some age-related disease decreases its prevalence as the population ages, as expected, since subjects with deleterious genotype are weeded out due to mortality. There exists, however, a set of age-related genes whose deleterious genotype indeed decreases up to ages 80–85, but subsequently increases monotonically, until by age 100 its prevalence is similar to that at age ∼60. Why is a known harmful genotype so prevalent among centenarians? Most likely because this genotype is protected by longevity genes. We corroborated this hypothesis by studying gene–gene interactions between age-related disease genotypes and longevity genotypes. Our findings suggest that individuals with the favorable longevity genotype can have just as many deleterious aging genotypes as the rest of the population because their longevity genotype protects them from the harmful effects of the other. We identify genes contributing to extreme lifespan as well as their counterpart, age-related disease genes. Our findings provide a proof of concept for the utility of high-throughput methods, and for elucidating mechanisms by which longevity genes buffer the effects of disease genes. Our approach gives hope for developing new medications that will protect against several age-related diseases.