Get started with custom lists to organize and share courses.

Sign up

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

  • Provider Coursera
  • Subject Bioinformatics
  • Cost Free Online Course (Audit)
  • Session Upcoming
  • Language English
  • Certificate Paid Certificate Available
  • Effort 4-6 hours a week
  • Start Date
  • Duration 4 weeks long
  • Learn more about MOOCs

Taken this course? Share your experience with other students. Write review

Overview

Sign up to Coursera courses for free Learn how

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

Tags

Help Center

Most commonly asked questions about Coursera Coursera

Reviews for Coursera's Algorithms for DNA Sequencing
4.5 Based on 17 reviews

  • 5 stars 88%
  • 4 star 0%
  • 3 star 0%
  • 2 star 0%
  • 1 stars 12%

Did you take this course? Share your experience with other students.

Write a review
  • 1
Mark W
5.0 3 years ago
by Mark completed this course, spending 5 hours a week on it and found the course difficulty to be medium.
Hello! I am a developer who's considering moving into bioinformatics. I took the course to get an understanding of the type of problems that computer scientists face in bio. Wanted to give you some feedback.

Pros

1:) Good introduction to the problems faced by computer scientists in bioinformatics. Got me very interested in the topic.

2:) Described the right amount of biology: enough to understand problem, but definitely geared towards algorithm side.

3:) Actual description of the algorithms and their complexity was pretty clear.

2 people found
this review helpful
Was this review helpful to you? Yes
Daria D
5.0 4 years ago
by Daria completed this course.
This course deals with the algorithms employed by mapping and genome assembly programs commonly used. It was only after completing the course that I realised that the course instructor, Ben Langmead, is actually the first author of the bowtie paper which is one of the most commonly used programs for DNA mapping. The lecture material is extremely well explained and accessible both to students with a computational background and to biologists. The algorithms employed are much better explained than in some other bioinformatics courses on Coursera that deal with some similar topic (UCSD Specialisa…
2 people found
this review helpful
Was this review helpful to you? Yes
Dejan Đ
5.0 4 years ago
by Dejan completed this course.
I feel that I have been finally introduced to the real world problems, their potential solutions and the paths for the improvement of such solutions. I feel that I've learned a lot about implementing the knowledge I've acquired so far and not only the knowledge gained through the specialization courses I've completed, and, more importantly, I feel myself much more drawn to the field of computational molecular biology and genomics than I ever was before. The only thing the course is missing is more of the same. I highly recommend the course for anyone interested in making first steps in serious…
1 person found
this review helpful
Was this review helpful to you? Yes
Leif U
5.0 3 years ago
Leif completed this course, spending 6 hours a week on it and found the course difficulty to be medium.
I have taken six other courses in this JHU Genomics series on Coursera and many others in Data Science @ JHU, Cybersecurity @ the U of Maryland etc on Coursera. I think this module is one of the very best I have taken. The video lectures with theory, explanations, and the implementation practicals are excellent. Just the right length lecture modules with crisp explanations and examples. The Quiz and Programming HW assignment content and approach reinforces making sure one understands the key concepts. The learning/frustration quotient on this class is very high. The Python HW programming assignments have all been challenging and fun. The final one is terrific and getting the virus back from BLAST was a blast - giving one a taste of the excitement of scientific discovery.
2 people found
this review helpful
Was this review helpful to you? Yes
Tyler D
5.0 4 years ago
Tyler completed this course.
A solid course from a great instructor. Unlike some of the other courses in the Genomic Data Science Specialization, which have been shallow or poorly taught, this course is challenging (but not undoable) and the lectures are very well organized.

The course is short, so you should not expect to get a full introduction to the field. But for its length, the course delivers a lot.
1 person found
this review helpful
Was this review helpful to you? Yes
Anonymous
5.0 4 years ago
Anonymous completed this course.
Good course for all levels. Not much previous experience needed and a good learning curve. Recommended for people of all backgrounds who want to learn how sequencing works.
1 person found
this review helpful
Was this review helpful to you? Yes
Allison C
5.0 3 years ago
Allison completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
This was a very nice course. The instructor explained things really well and the problem sets were fun, interesting, challenging enough to be motivating but doable. I had taken the San Diego bioinformatics courses, and this course helped me solidify some of the material that flew by in that other course. Highly recommended!
Was this review helpful to you? Yes
Anonymous
5.0 4 years ago
Anonymous completed this course.
This course was organized excellently. For a course with a duration of just 4 weeks it covers an amazing amount of required DNA sequencing background material and algorithms. Lectures were great and practicals were amazing since they covered coding of algorithms. Course offers plenty of scope for future learning.
Was this review helpful to you? Yes
Chrys C
5.0 2 years ago
by Chrys completed this course.
Really good course. Compared to the other courses in the specialisation this one is really awesome and helpful. The other python course does not prepare you for the level of this course because it gets quite tricky , quite fast but stick with it. The instructors are amazing and really cool.
Was this review helpful to you? Yes
Anonymous
5.0 3 years ago
Anonymous completed this course.
I found the lectures and the assignments to be very helpful and interesting. The course also provided an excuse to learn some of the Python programming language, which I encounter from time to time in my current career.
Was this review helpful to you? Yes
Alexander G
5.0 4 years ago
by Alexander completed this course, spending 16 hours a week on it and found the course difficulty to be medium.
Great course.

Thanks to wonderful instructors:

Ben Langmead, PhD and Jacob Pritt.

Highly recommended to all interested in algorithms design in general, applied computer science and modern bioinformatics.
Was this review helpful to you? Yes
Colin K
5.0 3 years ago
by Colin completed this course and found the course difficulty to be medium.
This was the high point of an otherwise dreadful specialization. It was well-taught. And both the exercises & tutorial format were well-suited to the course.
Was this review helpful to you? Yes
Radu D
5.0 4 years ago
by Radu completed this course.
1 person found
this review helpful
Was this review helpful to you? Yes
Anonymous
1.0 3 years ago
Anonymous is taking this course right now.
This course has a serious problem for anyone who has only taken the previous Introduction to Python course. This course fails to cover how to install and use the Python IDE (e.g. Anaconda, Jupyter, Notebook). The instructors just go ahead and present material in Notebook without showing how to load it, creating, or edit it. They were unable to explain the errors and grayed-out controls that I asked them about. They are unresponsive to questions. Answers were often variations on "you're really close" which is pointless. They do not seem to know how they got their own tools set up and now are unable to state a simple series of steps and configuration settings. Consequently, I come away feeling that the Python language and tool suite is not suitable for real-world work. It is a patchy academic introductory teaching tool at best.
0 person found
this review helpful
Was this review helpful to you? Yes
Anonymous
1.0 4 years ago
Anonymous completed this course.
As any course in both "specializations" from Johns Hopkins, this is a just a random collection of things with no structure. Don't waste your time, you will not learn much.
1 person found
this review helpful
Was this review helpful to you? Yes
Anonymous
5.0 4 years ago
Anonymous completed this course.
Was this review helpful to you? Yes
Chema C
5.0 4 years ago
by Chema completed this course.
Was this review helpful to you? Yes
  • 1

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free

Never stop learning Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.