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Updated: Mar 5, 2026

Pattern-based Search of Epigenomic Data Using GeNemo
Published on: October 8, 2017
Potential energy landscapes identify the information-theoretic nature of the epigenome
Garrett Jenkinson1,2, Elisabet Pujadas1,3, John Goutsias2
1Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Abstract:
Epigenetics is the study of biochemical modifications carrying information independent of DNA sequence, which are heritable through cell division. In 1940, Waddington coined the term "epigenetic landscape" as a metaphor for pluripotency and differentiation, but methylation landscapes have not yet been rigorously computed. Using principles from statistical physics and information theory, we derive epigenetic energy landscapes from whole-genome bisulfite sequencing (WGBS) data that enable us to quantify methylation stochasticity genome-wide using Shannon's entropy, associating it with chromatin structure. Moreover, we consider the Jensen-Shannon distance between sample-specific energy landscapes as a measure of epigenetic dissimilarity and demonstrate its effectiveness for discerning epigenetic differences. By viewing methylation maintenance as a communications system, we introduce methylation channels and show that higher-order chromatin organization can be predicted from their informational properties. Our results provide a fundamental understanding of the information-theoretic nature of the epigenome that leads to a powerful approach for studying its role in disease and aging.
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