Systemwide functional and structural changes caused by the aging process encourage the implementation of new bioinformatics search strategies for markers of aging. Combinatorial biomarkers should be particularly favored, as they can quantify processes on multiple levels of biological organization and overcome an otherwise limited ability to access heterogeneities in populations. An even more challenging but rational approach is the development of systems biology models to describe molecular pathways and key networks mechanistically as they relate to age. Such reverse engineered models not only indicate critical and diagnostic components (that is, potential biomarkers) but also should be able to predict the progression of aging through computer simulation.