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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Pricing
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
Ratings and Reviews
Great teaching, very interesting content. Only missing some checking of the contents (homework pages especially).
Excellent course, great teachers, the topics have been exposed smoothly for every level of expertise at bioinformatics. Hoping they make a second part with the others nice videos the teacher has in his Youtube channel.
Great course. For the complexity of the subject, the presentations are relatively easy to follow because the teacher is articulate and clear and the slide decks are informative. The homework assignments are challenging but not frustratingly so. I would recommend some familiarity with a programming language (although knowledge of Python in particular is not necessary) and some interest in bioinformatics.
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RP
This is the one course out of the genomics data science specialization that I found easy to follow and informative. The quizzes were challenging, but provided enough from the lectures to solve yourself.