Definition and characterization of the role of Epigenetic mechanisms have gained immense momentum since the completion of the Human Genome Project. The human epigenetic layer, made up of DNA methylation and multiple histone protein modifications, (the key elements of epigenetic mechanisms), is known to act as a switchboard that regulates the occurrence of most cellular events. In multicellular organisms such as humans, all cells have identical genomic contents but vary in DNA Methylation (DM) profile with the result that different types of cells perform a spectrum of functions. DM within the genome is associated with tight control of gene expression, parental imprinting, X-chromosome inactivation, long-term silencing of repetitive elements and chromatin condensation. Recently, considerable evidence has been put forward to demonstrate that environmental stress implicitly alters normal interactions among key epigenetic elements inside the genome. Aberrations in the spread of DM especially hypo/hyper methylation supported by an abnormal landscape of histone modifications have been strongly associated with Cancer initiation and development. While new findings on the impact of these key elements are reported regularly, precise information on how DM is controlled and its relation to networks of histone modifications is lacking. This has motivated modelling of DNA methylation and histone modifications and their interdependence. We describe initial computational methods used to investigate these key elements of epigenetic change, and to assess related information contained in DNA sequence patterns. We then describe attempts to develop a phenomenological epigenetic "micromodel", based on Markov-Chain Monte Carlo principles. This theoretical micromodel ("EpiGMP") aims to explore the effect of histome modifications and gene expression for defined levels of DNA methylation. We apply this micromodel to (i) test networks of genes in colon cancer (extracted from an in-house database, StatEpigen), and (ii) to help define an agent-based modelling framework to explore chromatin remodelling (or the dynamics of physical rearrangements), inside the human genome. Parallelization techniques to address issues of scale during the application of this micromodel have been adopted as well. A generic tool of this kind can potentially be applied to predict molecular events that affect the state of expression of any gene during the onset or progress of cancer. Ultimately, the goal is to provide additional information on ways in which these low level molecular changes determine physical traits for mormal and disease conditions in an organism.