Coursera
Free Online Course (Audit)
English
Paid Certificate Available
4 weeks long, 12 hours worth of material
selfpaced
Overview
Class Central Tips
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.
Syllabus
- 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.
Taught by
Ben Langmead and Jacob Pritt
