AutomationBioResearch - Ray and Stephanie Lane Center for Computational Biology - Carnegie Mellon University

02-450/02-750 - Automation of Biological Research: Robotics and Machine Learning

Instructor: Robert F. Murphy
Co-instructor: Armaghan "Rumi" Naik

Fall 2013
02-450: 9 units
02-750: 12 units

TuTh 3:00 pm to 4:20 pm, GHC 4101

Biology is increasingly becoming a "big data" science, as biomedical research has been revolutionized by automated methods for generating large amounts of data on diverse biological processes. Integration of data from many types of experiments is required to construct detailed, predictive models of cell, tissue or organism behaviors, and the complexity of the systems suggests that need for these models to be constructed automatically. This requires iterative cycles of acquisition, analysis, modeling, and experimental design, since it is not feasible to do all possible biological experiments. This course will cover a range of automated biological research methods (especially high-throughput, robotic methods for protein structure determination, gene sequencing, cell-based drug screening, and nanoassays), and a range of computational methods for automating the acquisition and interpretation of the data (especially active learning, proactive learning, compressed sensing and model structure learning). It assumes a basic knowledge of machine learning. Class sessions will consist of a combination of lectures and discussions of important research papers. Grading will be based on class participation, homeworks, and a final project.

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