Aging is a multifactorial condition that results in the loss of an organism's fitness over time. Different theories have been formulated to explain the mechanisms of aging, but a synthesis of these theories has not been possible until now. In addition, the increase in molecular data gathered by proteomics projects utilizing different organisms has permitted a better picture of proteins that function in aging. In this sense, the yeast Saccharomyces cerevisiae is a biological model for aging, and it shows two distinct aging states: a replicative state termed the replicative lifespan (RLS) and a quiescent state known as the chronological lifespan (CLS). Interestingly, both RLS and CLS appear to share common groups of proteins, but a combined model of both aging mechanisms has not been defined. Thus, by applying systems biology tools that allow mining of the yeast proteins associated with aging, it was possible to obtain an interactome network in which both RLS and CLS are represented. In addition, four subgraphs comprising ubiquitin-dependent proteasome/regulation of cell growth, nucleic acid metabolism, carbohydrate metabolism/RNA metabolism, and carbohydrate-organic acid-amino acid/DNA metabolism were found within the interactome, defining a new model of aging for yeast termed the chronologic-replicative protein network (CRPN).