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This project will be devoted to an exploration of modern methods in machine learning, a field at the interface of computer science and statistics. Specifically, we are interested in applying these methods to biological data sets that our group has already produced and studied. An example of such a project would be methods for learning time-varying networks from data, and applying them to a time course of microarray gene expression data from cells in response to drug doses.
This project will be most suitable for a computer science student with training and interest in machine learning. The more courses in computer science and statistics the student has, the better. An interest in biology is highly desirable but not strictly necessary.
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