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
MD
Nov 10, 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.
LK
Mar 12, 2016
Excellent intro to the computational challenges in analyzing genomic sequences.\n\nLectures and programming exercises explain algorithms very clearly even for beginners.
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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