02-251 Great Ideas in Computational Biology
12 units, Carnegie Mellon University
This 12unit course provides an introduction to many of the great ideas that have formed the foundation for the recent transformation of life sciences into a fullyfledged computational discipline. Extracting biological understanding from both large and small data sets now requires the use and design of novel algorithms, developed in the field of computational biology. This gateway course is intended as a first exposure to computational biology for firstyear undergraduates in the School of Computer Science, although it is open to other computationally minded 6students who are interested in exploring the field. Students will learn fundamental algorithmic and machine learning techniques that are used in modern biological investigations, including algorithms to process string, graph, and image data. They will use these techniques to answer questions such as How do we reconstruct the sequence of a genome, How do we infer evolutionary relationships among many species, and How can we predict each genes biological role on biological data. Previous exposure to molecular biology is not required, as the instructors will provide introductory materials as needed. After completion of the course, students will be well equipped to tackle advanced computational challenges in biology.
Prerequisites: (02-120 or 15-112) and (21-128 or 15-151 or 21-127)
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