Genomics and computational biology lie at the center of a rapid convergence of biomedical research fields. These disciplines take as their subject the entire genome (as DNA) or the entire material determined by genes (as RNA or protein), and ask about the origins, function, and interactions of the system as a whole. Questions like these, and other developments in this field, stimulate both experimental laboratory work and theoretical computational work. Studies in this field therefore require skills not only in the biological and biomedical areas, but also in computer science, mathematics, statistics, and engineering. Together, genomics and computational biology represent some of the most important new developments in science, and especially draw attention to cross-disciplinary areas of science.
The emerging field of genomics aims to accelerate the pace of research in biology and medicine through the application of advanced technologies for high-throughput data generation, novel measurements, and analysis. The massive amount of data generated by these technologies requires the integration of novel technologies, instrumentation, and laboratory automation with information management, modeling, analysis, and visualization tools. Often to gain the economies of scale expected of a genomics approach requires laboratory management skills and an understanding of automation techniques not available through traditional laboratory experiences. But most importantly, genomics must be grounded in a sound and thorough education in molecular, cellular, and organism biology (including genetics), combined with a solid foundation in the quantitative skills of mathematics, statistics, chemistry, and engineering. Computational Genomics requires additional training in computer science and software engineering. Our goal is to provide a comprehensive training program in Genomics and Computational Biology tha
Middle States Association of Colleges and Schools, Middle States Commission on Higher Education