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.
Module 3 Introduction
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Skills You'll Learn
Bioinformatics Algorithms, Algorithms, Python Programming, Algorithms On Strings
Reviews
4.7 (808 ratings)
- 5 stars80.81%
- 4 stars14.85%
- 3 stars2.97%
- 2 stars0.49%
- 1 star0.86%
NF
Mar 9, 2021
very engaging and well-presented course material.
intermediate difficulty while conveying the basics of how even recent real-world genome alignment and assembly tools work. great course design!
MY
Oct 9, 2020
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!
From the lesson
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.
Taught By
Ben Langmead, PhD
Assistant Professor
Jacob Pritt
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