This interdisciplinary course provides a hands-on approach to students in the topics of bioinformatics and proteomics. Lectures and labs cover sequence analysis, microarray expression analysis, Bayesian methods, control theory, scale-free networks, and biotechnology applications. Designed for those with a computational and/or engineering background, it will include current real-world examples, actual implementations, and engineering design issues. Where applicable, engineering issues from signal processing, network theory, machine learning, robotics and other domains will be expounded upon.
This class covers analysis of kinetics and dynamics of molecular and cellular processes across a hierarchy of scales, including intracellular, extracellular, and cell population levels; a spectrum of biotechnology applications are also taken into consideration. Topics include gene regulation networks; nucleic acid hybridization; signal transduction pathways; and cell populations in tissues and bioreactors. Emphasis is placed on experimental methods, quantitative analysis, and computational modeling.
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