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. 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
What you'll learn
- Apply quantitative methods to biological problems
- Define computational vocabulary
- Write Python, MATLAB, and R code to analyze biological data
- Examine any protein structure in PyMOL
- Analyze how to answer a scientific question through a step-by-step thought process.
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| Rating | 5.0★ based on 3 ratings |
|---|---|
| Length | 9 weeks |
| Effort | 9 weeks, 4–8 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $99 |
| From | Massachusetts Institute of Technology, MITx via edX |
| Instructors | Jeff Gore, Paul Blainey, Eric S. Lander, Ernest Fraenkel, Mary Ellen Wiltrout, Nathaniel Schafheimer |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Science |
| Tags | Biology & Life Sciences |
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What people are saying
applications rather than content
This terrific offering from MIT is unusual in being organized around applications rather than content -- each of the 8 weekly units introduces a different tool used by quantitative biologists, and each week's course topic serves both as a vehicle for hands-on experience with the tool as well as an engaging subject for learning.
organizing principle or constraint
What really makes this course are the varied and interesting topics, with no overall organizing principle or constraint, and the quality of the instruction and materials, which are, as is typical for MIT, first-rate.
assume no prior background
But the progressively organized materials assume no prior background and skeleton code is always provided; you're never just thrown into the deep water.
being organized around applications
what really makes
address larger questions
In some cases, the instructional videos are drawn from other MIT courses, and there are also "faculty perspective" videos that address larger questions in biology.
never just thrown
weekly units introduces
starmapping genetics simulator
The tools are Matlab, ImageJ, PyMol, the StarMapping genetics simulator, and the Python and R programming languages as used by biologists; and the topics include population modeling, equilibrium kinetics, molecular modeling, genetics, and disease prediction.
those familiar
Those familiar with programming in Matlab and Python will find those assignments pretty easy; newcomers will be challenged.
always provided
deep water
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Tools Administrator $58k
Quantitative Tutor $82k
Quantitative Specialist $99k
Project Tools $101k
Quantitative Analyst 3 $109k
Quantitative C++ Developer $109k
Tools & Engineering $126k
Tools Engineer 2 $133k
Methods and Tools $134k
Quantitative Development $134k
Quantitative Researcher, Growth $136k
Quantitative Marketing $137k
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| Rating | 5.0★ based on 3 ratings |
|---|---|
| Length | 9 weeks |
| Effort | 9 weeks, 4–8 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $99 |
| From | Massachusetts Institute of Technology, MITx via edX |
| Instructors | Jeff Gore, Paul Blainey, Eric S. Lander, Ernest Fraenkel, Mary Ellen Wiltrout, Nathaniel Schafheimer |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Science |
| Tags | Biology & Life Sciences |
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