The main focus of the research in this thesis is the investigation in DNA methylation mechanisms of epigenetics and the study of a specific database. As part of the latter work, the role of curation is described, and a new knowledge management system, PathEpigen1 , is reported that is currently being developed for colon cancer in the Sci-Sym centre. The database deals with genetic and epigenetic interactions and contains considerable data on molecular events such as genetic and epigenetic events. The data curation includes biomedical and biological information. An efficient method was devised to extract biological information from the literature to process, manage and upgrade data. We present a Deterministic Finite Automata (DFA) model for the DNA methylation mechanism controlled by DNA methyltransferase (DNMT) enzymes. This thesis provides a brief introduction to epigenetics, a survey of ongoing research on computational epigenetics and a description of the DNA methylation database. Furthermore, it also gives an overview of DNA methylation and its importance in cancer. The DFA models three states of methylation frequency (normal, de-novo and hypermethylated) in the cell. It has been executed on input of random strings of size 100. Out of the strings considered, we found that 26%, 37% and 37% correspond to normal, de-novo (cancer initiation) and hypermethylated (cancer) states, respectively.