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.
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About this Course
Learner Career Outcomes
43%
33%
Skills you will gain
Learner Career Outcomes
43%
33%
Offered by

Johns Hopkins University
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.
Syllabus - What you will learn from this course
DNA sequencing, strings and matching
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.
Preprocessing, indexing and approximate matching
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
Edit distance, assembly, overlaps
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.
Algorithms for assembly
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.
Reviews
TOP REVIEWS FROM ALGORITHMS FOR DNA SEQUENCING
This course provided me a very quick overview of all the core concepts pertaining to DNA sequencing. It is very well organized, crystal clear demonstration of concepts and I really enjoyed the course.
Very good course this is. Just a little advice, please make the quiz questions more clear and more specific because one shouldn't waste time to understand a question which is very easy to implement.
One of the most useful courses I have joined. Many thanks to the instructors for these quality lectures and for the time spent to deliver the information as easily as possible!
Highly eloquent instructors that make intricate concepts accessible and fun to learn. Would definitely help if you have some programming or bioinformatics background beforehand.
About the Genomic Data Science Specialization
With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome.

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