A workshop-style introduction to tools used in biological research. Discover how to analyze data using computational methods.
Welcome to 7.QBWx: Quantitative Biology Workshop, an exciting and innovative course offered by MITx that bridges the gap between biology and computational methods. This intermediate-level course is designed to introduce learners to the fascinating world of quantitative biology, where cutting-edge computational tools are applied to solve complex biological problems.
While programming experience is not required, students should have completed 7.00x Introduction to Biology or have equivalent knowledge in biochemistry, molecular biology, and genetics. The course will provide introductions to MATLAB, Python, and R programming languages.
This course is ideal for students with an interest in biology and quantitative tools, as well as those with computational backgrounds looking to apply their skills to biological problems. It's also perfect for biology students who want to understand how scientists analyze complex data using computational methods.
The skills acquired in this course are highly valuable in today's interdisciplinary scientific landscape. Students will be able to:
This course provides a unique opportunity to gain hands-on experience with the same tools and programs used by professional scientists. By completing this workshop, learners will be well-equipped to explore further studies in computational biology, bioinformatics, or related fields, and will have a competitive edge in the rapidly evolving field of biological sciences.
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Drugs are biologically active compounds. Drug discovery and drug development rely on methods for measuring biological activity. The term “activity” is quite general. In practice, a substance’s biological activity can refer to how a substance affects a biological pathway, cell-level responses, safety risks, how long a substance resides within in a system, as well as a substance’s effects in an organism (called pharmacodynamics). The design of methods for measuring activity is a critical aspect of drug discovery. The design of robust and informative methods can accelerate the drug discovery and development process.
