About this course: 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.
Created by: Johns Hopkins University
Taught by: Ben Langmead, PhD, Assistant Professor
Computer Science
Taught by: Jacob Pritt
Department of Computer Science
| Basic Info |
Course 4 of 8 in the
Genomic Data Science Specialization.
|
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
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.
19 videos, 7 readings
Graded: Module 1
Graded: Programming Homework 1
WEEK 2
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
15 videos, 1 reading
Graded: Module 2
Graded: Programming Homework 2
WEEK 3
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.
13 videos, 1 reading
Graded: Module 3
Graded: Programming Homework 3
WEEK 4
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.
13 videos, 1 reading
Graded: Programming Homework 4
Graded: Module 4
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| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
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Ratings and Reviews
Great course! The materials explain everything from scratch. The Practical lessons are very helpful! Thank you for this course.
well explained
This is hands-down the best course in this specialization. There are good teachers (many of whom are teaching the other courses) and then there are the top 20% excellent teachers (Ben Langmead) who teaches this class. In addition to being an excellent computer scientist, he is also an excellent teacher and he makes the material interesting and approachable. The homework assignments are challenging, but created in such a way that the difficulty lies more in grappling with the concepts themselves, and less with debugging python code or whatever. I highly recommend this course, and hope that Ben will do a "Algorithms: Part Two" covering Burrows-Wheeler and going into more depth, maybe discussing pseudo-alignment as well.
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the course was clear and instructive. i've enjoyed every moment of it, thx to instructors.