Computational approaches based on statistical, mathematical and physical principles are now permeating all areas of biological and biomedical research. Driving this explosion in biological computation are new high-throughput techniques in genomics and proteomics, advances in live- cell imaging, and improved methods for studying structure-function relationships of biological molecules. Each of these fields generates complex data sets that require computational approaches to analyze and interpret. Therefore, there is large and increasing demand for a new generation of biomedical researchers with expertise in the analytic methods of scientific computing, statistics, physics and applied mathematics as well as training in the biological sciences. To address this need, in 2007 the University of North Carolina at Chapel Hill (UNC- CH) established the Ph.D. Curriculum in Bioinformatics and Computational Biology (BCB). The major Goal of the BCB curriculum is to train the next generation of scientists with the computational and quantitative skills required to make important contributions to modern biological and biomedical research. The BCB curriculum also strives to provide students with the professional skills required to succeed in an academic or industrial environment. The Ph.D. curriculum provides the necessary latitude to provide students with a broad over view of computational approaches in modern biology, while allowing them to gain in depth training in a particular area of bioinformatics or computational biology. The curriculum is unique at UNC-CH in that it draws faculty from more departments (18) and serves more academic units (5 schools and colleges) than any other training program. Because of its inherently interdisciplinary nature, the BCB curriculum has fostered multiple new collaborative research projects. To ensure continued success of the curriculum, funds are requested to support six predoctoral students per year. The requested funds will dovetail with UNC-CH's investment in computing infrastructure, faculty recruitment, and education in both bioinformatics and computational biology and will allow this vitally important interdisciplinary training program to continue to thrive and grow. Relevance Interpreting the large and complex data sets generated by modern experimental techniques in the biological sciences requires innovative computational and mathematical approaches. The Curriculum in Bioinformatics and Computational Biology at the University of North Carolina at Chapel Hill provides graduate training needed to develop and apply computational methods to cutting-edge problems in biomedical research.
Modern biomedical technologies, including rapid genome sequencing, high-content mass spectrometry, and modern microscopy, are allowing systems level analyses of complex diseases, such as cancer, heart disease and diabetes. Interpreting the large and complex data sets produced by these techniques requires novel computational and quantitative approaches. The Curriculum in Bioinformatics and Computational Biology at the University of North Carolina at Chapel Hill provides the graduate training needed to develop and apply computational methods for solving driving biomedical problems. These techniques may suggest novel therapeutic strategies for treating complex diseases.
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