The sequencing of the human genome is a highly acclaimed scientific accomplishment which provides the foundations for many decades of health research. Variations of human characteristics form the cornerstone of current genetic studies. However, the effective contribution of the human genome project to medical advances will require multiple experimental approaches to identify genetic variations associated with specific diseases. As a result of such large-scale projects, we need to manage, interpret and analyze vast amounts of experimental data. The development of computational technology and its application to biology have become essential for managing, interpreting and understanding such information. New high- performance computing with improved processing power using sophisticated programs has been developed all across the world to identify and interpret the vast amounts of data accumulated in genetic studies. Many of those experiments yield massive outflow of data and need to be properly designed and analyzed using highly efficient statistical and computational programs. The objectives of the present study are to develop new approaches using next-generation sequencing to address many important data analysis problems in epigenomics. The combination of the power of computer science and the knowledge of biology will be essential in understanding gene regulation of the human genome.