Abstract
This chapter will briefly address the history of systems biology and complexity theory and its use in understanding the dynamics of aging at the 'omic' level of biological organization. Using the idea of treating a biological organism like a network, we will examine how network mathematics, particularly graph theory, can provide deeper insight and can even predict potential genes and proteins that are related to the control of organismal life span. We will begin with a review of the history of network analysis at the cellular level and follow that by an introduction to the various commonly used network analysis variables. We will then demonstrate how these variables can be used to predict potential targets for experimental analysis. Lastly, we will close with some of the challenges that network methods face.
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