MATLAB for Biology: Quantitative Methods
Master MATLAB basics to analyze biological datasets, from simple data handling to complex visualizations, in this Harvard-designed primer for life scientists.
Master MATLAB basics to analyze biological datasets, from simple data handling to complex visualizations, in this Harvard-designed primer for life scientists.
Dive into the world of quantitative biology with this comprehensive MATLAB course from Harvard. Designed for biologists, health workers, and medical students new to programming, as well as experienced coders looking to apply their skills to biological problems. The course offers a unique learning experience, allowing you to study alongside other students learning to code. You'll master MATLAB basics, troubleshooting techniques, and their applications in biology and medicine. With free access to MATLAB Online during the course, you'll gain hands-on experience in data analysis, image processing, and biological modeling. Whether you're a complete beginner or an expert in other programming languages, this course provides a solid foundation in MATLAB for quantitative biology research.
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What you'll learn
Master the fundamentals of MATLAB programming
Develop skills in biological data analysis and visualization
Learn to process and analyze biological images using MATLAB
Create custom functions and scripts for biological applications
Apply quantitative methods to solve real-world biological problems
Gain proficiency in troubleshooting and debugging MATLAB code
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 11 modules in this course
This course provides a comprehensive introduction to MATLAB programming with a focus on biological applications. Students will learn the fundamentals of MATLAB, including arrays, loops, functions, and scripts. The course covers data collection and analysis techniques specific to biological research. Image processing, a crucial skill in many biological fields, is also addressed. Students will apply their skills to real-world biological problems, including a special project on yeast analysis. The course also covers advanced topics and provides references and tools for further learning. Throughout the course, emphasis is placed on troubleshooting code and developing practical programming skills for quantitative biology research.
Introduction to MATLAB
Module 1
Arrays
Module 2
Images
Module 3
Loops
Module 4
Functions and Scripts
Module 5
Data Collection and Analysis
Module 6
Arrays, pt 2
Module 7
Special Topics
Module 8
Yeast Showdown
Module 9
Pro Tips
Module 10
References and Tools
Module 11
Fee Structure
Instructor
1 Course
Harvard Systems Biologist Leading Innovation in Cellular Research and COVID-19 Response
Michael Springer, a Professor of Systems Biology at Harvard Medical School and co-director of HIVE, has established himself as a pioneering researcher and educator in cellular biology and systems analysis. After earning BS degrees in Chemistry and Biology from Stanford in 1996 and a PhD in Cell Biology from UC San Francisco in 2003, he has built an impressive career studying how evolution shapes cellular responses to environmental changes. His research encompasses yeast species analysis using advanced techniques like in vivo fluorescence and genetic approaches. Dr. Springer's contributions extend beyond traditional research, as he co-developed a computational skills course that has reached over 1,000 in-person students and 30,000 online learners. His work has earned support from prestigious organizations including NIH, NSF, DARPA, and IARPA. During the COVID-19 pandemic, he made remarkable contributions by developing novel sample collection technology, establishing Harvard's first CLIA certified lab, and overseeing more than 2.2 million COVID-19 tests in its first year. His current research focuses on developing new diagnostics and advancing microbial engineering for sustainable production, including innovative approaches to bioweathering for carbon dioxide removal and local food production.
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4.8 course rating
16 ratings
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