Comparing Genes, Proteins, and Genomes (Bioinformatics III)

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Comparing Genes, Proteins, and Genomes (Bioinformatics III)

Course Details

Cost

FREE

Upcoming Schedule

  • 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
4680 reviews

Course Description

After sequencing genomes, we would like to compare them. We will see that dynamic programming is a powerful algorithmic tool when we compare two genes (i.e., short sequences of DNA) or two proteins. When we "zoom out" to compare entire genomes, we will employ combinatorial algorithms.
Reviews 9/10 stars
1 Review for Comparing Genes, Proteins, and Genomes (Bioinformatics III)

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Steven Frank profile image
Steven Frank profile image
10/10 starsCompleted
  • 59 reviews
  • 57 completed
3 years ago
Having learned to sequence genes in the last course segment, this installment focuses on how to compare them -- an often-difficult task because a meaningful comparison must consider the possibility of mutations, sharply increasing the complexity of the task. How do you "align" sequences that have unlimited potential for variation? The solution is to be found in "dynamic programming," a powerful technique that is well-presented here. The text and programming assignments are more challenging than those of the earlier course segments, but they are taught clearly and progressively, and the staff is fabulous (I'm talking about you, Giampaolo Eusebi!). Graph theory can be esoteric and abstract, but when anchored to interesting problems in biology, it becomes a lot of fun. The course also covers rearrangements within genes and genomes, leading to ways to compare, say, human and mouse genomes, and more kinds of computational graphs. Th... Having learned to sequence genes in the last course segment, this installment focuses on how to compare them -- an often-difficult task because a meaningful comparison must consider the possibility of mutations, sharply increasing the complexity of the task. How do you "align" sequences that have unlimited potential for variation? The solution is to be found in "dynamic programming," a powerful technique that is well-presented here. The text and programming assignments are more challenging than those of the earlier course segments, but they are taught clearly and progressively, and the staff is fabulous (I'm talking about you, Giampaolo Eusebi!). Graph theory can be esoteric and abstract, but when anchored to interesting problems in biology, it becomes a lot of fun. The course also covers rearrangements within genes and genomes, leading to ways to compare, say, human and mouse genomes, and more kinds of computational graphs. The questions addressed in this course segment continue to be interesting biologically and now are more challenging computationally. It's all good.
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