Computational Biology provides students with a unique set of skills. It combines the rigor and algorithmic focus of traditional computer science with the data analysis, machine learning, and modeling skills required to understand a complex natural system. It teaches students to think computationally and to frame complex analysis questions in the language of computation. It also provides a deep understanding of biology so that students emerge as experts in biomedical problems. This prepares them to directly contribute in one of the many stimulating jobs in biotechnology/pharmaceutical industries and startups. It prepares them to deal with large, complex, imperfect data sets, a skill that is needed not just in biology but in a wide host of fields, from high-powered finance to data science.

For students considering Ph.D. programs in computational or systems biology, majoring in Computational Biology reduces the need for extensive coursework in the early years of a Ph.D. program, allowing them to tackle interesting research questions right away. Likewise, for students considering healthcare professions, majoring in computational biology provides extensive interdisciplinary training relevant to genomic medicine and personalized/precision medicine that will prepare them well for the changing landscape of healthcare practice (the curriculum has a great deal of overlap with typical pre-medical requirements). Better than single subject majors in computer science or biology, a degree in computational biology combines rigor in computer science with critical foundations in the natural sciences to provide the ideal solution for students who intend to pursue careers in biomedical research or healthcare.

Source: http://www.cbd.cmu.edu/education/bs-in-computational-biology/why-major-in-computational-biology/

Carnegie Mellon University | BS: Computational Biology

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