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Massachusetts Institute of Technology

Quantitative Biology Workshop

Massachusetts Institute of Technology via edX

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Overview

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. 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. We recommend that learners try to complete each week to find what interests them the most.

This workshop includes activities on the following biological topics: population biology, biochemical equilibrium and kinetics, molecular modeling of enzymes, visual neuroscience, global and single-cell gene expression, development, and genomics. The tools and programming languages include MATLAB, PyMOL, 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.

Workshop Content Creators and Residential Leaders

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

Residential Outreach Workshop Organizer and Creator

Mandana Sassanfar

Taught by

Jeff Gore

Reviews

4.7 rating, based on 6 Class Central reviews

4.3 rating at edX based on 9 ratings

Start your review of Quantitative Biology Workshop

  • Profile image for Suryaprakash
    Suryaprakash
    This Online course gave me a foundation for Some Dry lab Tools especially Python, R, and some visualization tools.
  • Anonymous
    An excellent course with great teachers who promote critical thinking through real and practical examples that help to better understand the subject matter, as well as allow a closer approach to science.
  • Anonymous
    Covers a very wide range of extremely interesting and important topics in quantitative biology. Lots of hands on work with various tools and environments. Great lectures and terrific course materials.
  • Anonymous
    I just finished 'Quantitative Biology' offered by MITx on edX. To summarise my learning experience, I found the learning content in this course challenging, comprehensive and of great value with respect to the total time I have invested for studying this course. I also received exposure to tutorials from Mathworks on MATLAB, on R and on Python.
    This course does not aim at covering scientific knowledge superficially, but focuses on equipping the learners with theoretical, experimental and analytical applications of the biological concepts. Hence, quantitative biology is truly meant for those who are aspiring to have a career in scientific research.
  • Anonymous
    This is an excellent course it helped me to grow up in my career because there are many things that I didn't know that existed and new techniques to continue learning. There are very difficult topics but the way they explain is really good even if you don't know anything of programming or biology

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