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Aging biology finds itself in a post-genomic era. Hopes of bringing methods developed in mathematics, physics or statistics into the biology realm are widespread. The goal and unifying theme of this work is to get a better understanding of the new and exiting field of aging as a complex process, using quantitative methods. By combining molecular and biophysical modeling with statistical and mathematical tools, my goal is to provide a multi-scale view of the complex biological process that is aging. The approach I am taking involves consideration of the problem on several levels--from transcriptional regulation of gene expression, modeling of biological pathways and interaction networks, to the development of mathematical and statistical methods; from trying to understand the aging process at a transcriptional level, and analyzing how stochastic factors might come to play a role in aging and in its understanding as an epigenetic process.