Genome Assembly Programming Challenge

This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs. Sorry, we do not believe in multiple choice questions when it c

Created by: Alexander S. Kulikov

icon
Quality Score

Content Quality
/
Video Quality
/
Qualified Instructor
/
Course Pace
/
Course Depth & Coverage
/

Overall Score : 78 / 100

icon
Course Description

In Spring 2011, thousands of people in Germany were hospitalized with a deadly disease that started as food poisoning with bloody diarrhea and often led to kidney failure. It was the beginning of the deadliest outbreak in recent history, caused by a mysterious bacterial strain that we will refer to as E. coli X. Soon, German officials linked the outbreak to a restaurant in LAbeck, where nearly 20% of the patrons had developed bloody diarrhea in a single week. At this point, biologists knew that they were facing a previously unknown pathogen and that traditional methods would not suffice - computational biologists would be needed to assemble and analyze the genome of the newly emerged pathogen.To investigate the evolutionary origin and pathogenic potential of the outbreak strain, researchers started a crowdsourced research program. They released bacterial DNA sequencing data from one of a patient, which elicited a burst of analyses carried out by computational biologists on four continents. They even used GitHub for the project: https://github.com/ehec-outbreak-crowdsourced/BGI-data-analysis/wikiThe 2011 German outbreak represented an early example of epidemiologists collaborating with computational biologists to stop an outbreak. In this Genome Assembly Programming Challenge, you will follow in the footsteps of the bioinformaticians investigating the outbreak by developing a program to assemble the genome of the E. coli X from millions of overlapping substrings of the E.coli X genome.Do you have technical problems? Write to us: [email protected]

icon
Instructor Details

Alexander S. Kulikov

Alexander S. Kulikov is a research fellow at St. Petersburg Department of Steklov Mathematical Institute of the Russian Academy of Sciences and a visiting professor at University of California, San Diego. His scientific interests include algorithms for NP-hard problems and circuit complexity. In St. Petersburg, he runs Computer Science Club and Computer Science Center.

icon
Reviews

3.9

31 total reviews

5 star 4 star 3 star 2 star 1 star
% Complete
% Complete
% Complete
% Complete
% Complete

By Jose P E on 2-Nov-17

Very nice applications of the algorithms learned during the specialization.You won't get help from the instructors, but hopefully from the students. Besides, since this is the "capstone project", you are supposed to do it by yourself.The only negative point is that at the beginning of the specialization, they announced that there were going to be different options for the capstone project. This one is more like a regular course.But I learned interested applications of the algorithms I learned, and I'm happy for it.

By Tamilarasu S on 25-Apr-18

Very good collection of problems for a finale.Though you would not be assembling human genome, you will be exposed to the challenges faced during a real genome assembly of a bacterial genome.A very theoretical specialization ending with practical problems.

By Joseph G N on 19-Sep-18

Nice exercises were difficult and interesting. You can learn a lot of in this course not only to solve bioinformatic problems

By Tamas S on 8-Jun-19

Felt a little bit adrift from the general flow of topics in the other courses. Of course this called a challenge for a reason, but it's funny that you can pass this course doing barely anything actually related to genome assembly as there are other problems for each week as well.

By Teguh S on 29-Nov-16

The problems are interesting, the course is great. However, the problem sets in this programming challenge are often not so well-defined, which makes it really difficult to solve (especially the dataset problem). The solution of the problems usually turns out to be quite simple, but is not applicable to a large set of problems, only to the particular dataset that is given (and the characteristics of this dataset is not given; so I end up thinking about all possibilities that might occur for that dataset, which makes the problem more difficult). The examples given in the problem set are also not sufficient to describe the characteristics of the problem clearly. However, I really appreciate the whole courses, and I think it has been a great experience to go through the courses! Thank you very much!

By John B on 15-Jun-18

There were countless errors in the descriptions of the programming problems, not just "ambiguities" or "open ended problem definitions" but quantitatively incorrect specific statements (length of inputs, structure of inputs, etc). Many of these issues have been pointed out in the forums, but remain uncorrected as of June 2018.

By Alexandr S on 5-Aug-18

I would like to say thank you to all who have created this course and specialization! Good material, excellent lecturers!

By Zac B on 4-Oct-18

Most challenging course I've taken on Coursera so far, so be prepared. However, I'm definitely a far better programmer due to it! <3 Thanks to the instructors for great material and well designed challenges.

By Madan K on 27-Feb-17

Really Challenging course, will make the mind to work.Enjoyed taking the course, was much harder than expected and loved it anyway.Worth the time ,effort and resources.The course was much less guided compared to other the course but instructor mentioned it that it was on purpose for developing self learning and facing real life sitituations.

By Pavel O on 4-Aug-17

Good course and final capstone project. Would recommend anyone from beginner to professional.

By Ahmad B E on 17-Jan-18

This is how algorithms should be.

By Pradyumn A on 14-Jul-17

Really tough and enjoyable Project. Learnt something very special.