From GrailSearch, an enthusiastic look at the role of bioinformatics in the mainstream approach to tackling aging by manipulating genes and metabolism: "The golden age of biology is upon us. We have broken through what previously seemed like an impenetrable wall of complexity, size and scale by decoding the human genome and are now building the next generation of tools to tackle the subsequent set of challenges. The most significant of these hurdles is that of aging. It also happens to be humanity's most important problem to tackle as most human suffering stems from this unfortunate and unnecessary process. The best tool we have for understanding the complex biological networks of aging is computational theory, particularly machine learning and its application to Systems Biology. Computational horsepower via high-performance computing, machine learning algorithms and biological data are all reaching a point where the intersection of these will soon allow us to use computational systems approaches for developing predictive models that precisely illustrate how we can tweak biological networks to best affect the dreaded aging process."