Quantitative Biology Workshop

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Quantitative Biology Workshop

Do you have an interest in biology and quantitative tools? Do you know computational methods but do not realize how they apply to biological problems? Do you know biology but do not understand how scientists really analyze complicated data? 7.QBWx: Quantitative Biology Workshop is designed to give learners exposure to the application of quantitative tools to analyze biological data at an introductory level. For the last few years, the Biology Department of MIT has run this workshop-style course as part of a one-week outreach program for students from other universities. With 7.QBWx, we can give more learners from around the world the chance to discover quantitative biology. We hope that this series of workshops encourages learners to explore new interests and take more biology and computational courses.



We expect that learners from 7.00x Introduction to Biology – The Secret of Life or an equivalent course can complete this workshop-based course without a background in programming. The course content will introduce programming languages but will not teach any one language in a comprehensive manner. The content of each week varies. We want learners to have an introduction to multiple languages and tools to find a topic that they would want to explore more. Participants with programming experience will find some weeks easier than students with only biology experience, while those with a biology background should find the week on genetics easier. We recommend that learners try to complete each week to find what interests them the most.



Workshop Content Creators and Residential Leaders



Gregory Hale, Michael Goard, Ph.D., Ben Stinson, Kunle Demuren, Sara Gosline, Ph.D., Glenna Foight, Leyla Isik, Samir El-Boustani, Ph.D., Gerald Pho, and Rajeev Rikhye



Residential Outreach Workshop Organizer and Creator



Mandana Sassanfar, Ph.D.



This workshop includes activities on the following biological topics: population biology, biochemical equilibrium and kinetics, molecular modeling of enzymes, visual neuroscience, genetics, gene expression and development, and genomics. The tools and programming languages include MATLAB, PyMOL, StarGenetics, Python, and R. This course does not require learners to download MATLAB. All MATLAB activities run and are graded within the edX platform. We do recommend that participants download a few other free tools for the activities so that they learn how to use the same tools and programs that scientists use.



 


Categories: Life Sciences
Starts : 2016-10-04

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