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This course is part of Genomic Data Science Specialization
Instructors: Ben Langmead, PhD
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We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.
This module we begin our exploration of algorithms for analyzing DNA sequencing data. We'll discuss DNA sequencing technology, its past and present, and how it works.
19 videos7 readings2 assignments
In this module, we learn useful and flexible new algorithms for solving the exact and approximate matching problems. We'll start by learning Boyer-Moore, a fast and very widely used algorithm for exact matching
15 videos1 reading2 assignments
This week we finish our discussion of read alignment by learning about algorithms that solve both the edit distance problem and related biosequence analysis problems, like global and local alignment.
13 videos1 reading2 assignments
In the last module we began our discussion of the assembly problem and we saw a couple basic principles behind it. In this module, we'll learn a few ways to solve the alignment problem.
13 videos1 reading2 assignments
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Fred Hutchinson Cancer Center
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Johns Hopkins University
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Johns Hopkins University
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Johns Hopkins University
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919 reviews
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Reviewed on Nov 9, 2016
This was really fun. Really enjoyed the a-ha of the algorithms and the fun of solving the alignment and assembly problems. Feel mildly powerful after assembling a virus genome.
Reviewed on Sep 2, 2020
Very well explained, a lot of the gaps of the previous courses got cleared up. This course should be an example on how to teach a subject. Thanks!!!
Reviewed on Jul 3, 2018
Very well prepared, from basics up to all commonly used techniques in bioinformatics. Prerequisites in Python is a plus, but not even necessary.
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