Genome Sequencing (Bioinformatics II)

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Course Details

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FREE

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  • On demand

Course Provider

Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4679 reviews

Course Description

Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read short pieces of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces. We will further learn about brute force algorithms and apply them to sequencing mini-proteins called antibiotics. Finally, you will learn how to apply popular bioinformatics software tools to sequence the genome of a deadly Staphylococcus bacterium.
Reviews 9/10 stars
1 Review for Genome Sequencing (Bioinformatics II)

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Steven Frank profile image
Steven Frank profile image
10/10 starsCompleted
  • 59 reviews
  • 57 completed
3 years ago
This second installment of the six-part bioinformatics series focuses on sequencing. Gene and protein sequences are the axis around which all of biology turns, and the scale of the Human Genome Project gives a sense of how central a role computational analysis plays. What this course covers is well captured by the "exploding newspaper problem" -- how do you reconstruct the news from a newspaper that's been blown to smithereens? How can you reconstruct a huge DNA molecule from the short segments that can be generated and read? These are problems in graph theory, and this course provides a great introduction to what might otherwise seem esoteric and abstract by grounding theory in the practicalities of biology. As in all courses in this series, there's a "biologist" track and a "hacker" track, and for the latter, the programming assignments can be considerably more challenging than those in Bioinformatics I. But they're fun -- it... This second installment of the six-part bioinformatics series focuses on sequencing. Gene and protein sequences are the axis around which all of biology turns, and the scale of the Human Genome Project gives a sense of how central a role computational analysis plays. What this course covers is well captured by the "exploding newspaper problem" -- how do you reconstruct the news from a newspaper that's been blown to smithereens? How can you reconstruct a huge DNA molecule from the short segments that can be generated and read? These are problems in graph theory, and this course provides a great introduction to what might otherwise seem esoteric and abstract by grounding theory in the practicalities of biology. As in all courses in this series, there's a "biologist" track and a "hacker" track, and for the latter, the programming assignments can be considerably more challenging than those in Bioinformatics I. But they're fun -- it's very cool to see how graph theory works a kind of magic on problems whose scale makes them seem hopeless. Once again, the interactive textbook is excellent and the lectures, while worthwhile, are not essential. When most people think of bioinformatics, they probably think of gene sequencing, and this course is a great hands-on intro to the topic.
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