4 Classes (34 Units)

20.260 (6), 20.309 (12), 20.315 (12), 20.560 (4)

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20.260 Computational Analysis of Biological Data

Class Info

Presents foundational methods for analysis of complex biological datasets. Covers fundamental concepts in probability, statistics, and linear algebra underlying computational tools that enable generation of biological insights. Assignments focus on practical examples spanning basic science and medical applications. Assumes basic knowledge of calculus and programming.

This class has no prerequisites.

20.260 will not be offered this semester. It will be available during IAP.

This class counts for a total of 6 credits.

You can find more information at the MIT + 20.260 - Google Search site.

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20.309 Instrumentation and Measurement for Biological Systems

Class Info

Sensing and measurement aimed at quantitative molecular/cell/tissue analysis in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies, and electro-mechanical probes (atomic force microscopy, optical traps, MEMS devices). Application of statistics, probability, signal and noise analysis, and Fourier techniques to experimental data. Enrollment limited; preference to Course 20 undergraduates.

This class has 7.01x, 8.02, 6.0002, and 18.03 as prerequisites.

20.309 will be offered this semester (Fall 2018). It is instructed by P. Blainey, S. Manalis, E. Frank, S. Wasserman, J. Bagnall, E. Boyden and P. So.

Lecture occurs 12:00 PM to 13:00 PM on Tuesdays and Thursdays in 16-220.

This class counts for a total of 12 credits.

You can find more information at the MIT + 20.309 - Google Search site or on the 20.309 Stellar site.

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20.315 Physical Biology

Class Info

Focuses on current major research topics in quantitative, physical biology. Covers synthetic structural biology, synthetic cell biology, microbial systems biology and evolution, cellular decision making, neuronal circuits, and development and morphogenesis. Emphasizes current motivation and historical background, state-of-the-art measurement methodologies and techniques, and quantitative physical modeling frameworks. Experimental techniques include structural biology, next-generation sequencing, fluorescence imaging and spectroscopy, and quantitative biochemistry. Modeling approaches include stochastic rate equations, statistical thermodynamics, and statistical inference. Students taking graduate version complete additional assignments.

This class has 5.60, and 20.110 as prerequisites.

20.315 will not be offered this semester. It will be available in the Spring semester, and will be instructed by J. Gore and I. Cisse.

Lecture occurs 11:00 AM to 12:30 PM on Mondays and Wednesdays in 4-257.

This class counts for a total of 12 credits.

You can find more information at the MIT + 20.315 - Google Search site.

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20.560 Statistics for Biological Engineering

Class Info

Provides basic tools for analyzing experimental data, interpreting statistical reports in the literature, and reasoning under uncertain situations. Topics include probability theory, statistical tests, data exploration, Bayesian statistics, and machine learning. Emphasizes discussion and hands-on learning. Experience with MATLAB, Python, or R recommended.

This class has no prerequisites.

20.560 will not be offered this semester. It will be available during IAP.

This class counts for a total of 4 credits. This is a graduate-level class.

You can find more information at the MIT + 20.560 - Google Search site.

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