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Intro

Coursera: Finding Hidden Messages in DNA (Bioinformatics I)

 with  Pavel Pevzner and Phillip Compeau
Class Central Course Rank
#2 in Subjects > Data Science > Bioinformatics

Named a top 50 MOOC of all time by Class Central!

This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat.

In the first half of the course, we investigate DNA replication, and ask the question, where in the genome does DNA replication begin? We will see that we can answer this question for many bacteria using only some straightforward algorithms to look for hidden messages in the genome.

In the second half of the course, we examine a different biological question, when we ask which DNA patterns play the role of molecular clocks. The cells in your body manage to maintain a circadian rhythm, but how is this achieved on the level of DNA? Once again, we will see that by knowing which hidden messages to look for, we can start to understand the amazingly complex language of DNA. Perhaps surprisingly, we will apply randomized algorithms, which roll dice and flip coins in order to solve problems.

Finally, you will get your hands dirty and apply existing software tools to find recurring biological motifs within genes that are responsible for helping Mycobacterium tuberculosis go "dormant" within a host for many years before causing an active infection.

Syllabus

Week 1: Welcome!

Welcome to class!

This course will focus on two questions at the forefront of modern computational biology, along with the algorithmic approaches we will use to solve them in parentheses:

  1. Weeks 1-2: Where in the Genome Does DNA Replication Begin? (Algorithmic Warmup)
  2. Weeks 3-4: Which DNA Patterns Play the Role of Molecular Clocks? (Randomized Algorithms)

Week 5 will consist of a Bioinformatics Application Challenge in which you will get to apply software for finding DNA motifs to a real biological dataset.

Each of the two chapters in the course is accompanied by a Bioinformatics Cartoon created by Randall Christopher and serving as a chapter header in the Specialization's bestselling print companion. You can find the first chapter's cartoon at the bottom of this message. What does a cryptic message leading to buried treasure have to do with biology? We hope you will join us to find out!

Phillip and Pavel



Week 2: Finding Replication Origins

Welcome to Week 2 of class!

This week, we will examine the biological details of how DNA replication is carried out in the cell. We will then see how to use these details to help us design an intelligent algorithmic approach looking for the replication origin in a bacterial genome.



Week 3: Hunting for Regulatory Motifs

Welcome to Week 3 of class!

This week, we begin a new chapter, titled "Which DNA Patterns Play the Role of Molecular Clocks?" At the bottom of this message is this week's Bioinformatics Cartoon.  What does a late night casino trip with two 18th Century French mathematicians have in common with finding molecular clocks?  Start learning to find out...



Week 4: How Rolling Dice Helps Us Find Regulatory Motifs

Welcome to Week 4 of class!

Last week, we encountered a few introductory motif-finding algorithms. This week, we will see how to improve upon these motif-finding approaches by designing randomized algorithms that can "roll dice" to find motifs.



Week 5: Bioinformatics Application Challenge
Welcome to week 5 of the class! This week, we will apply popular motif-finding software in order to hunt for motifs in a real biological dataset.

17 Student
reviews
Cost Free Online Course (Audit)
Subject Bioinformatics
Provider Coursera
Language English
Certificates Paid Certificate Available
Hours 4-10 hours a week
Calendar 5 weeks long
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17 reviews for Coursera's Finding Hidden Messages in DNA (Bioinformatics I)

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2 out of 3 people found the following review useful
2 years ago
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Jeff Lam completed this course and found the course difficulty to be easy.
For someone like me with a background in computer science/engineering, this course had great content introducing biological concepts and the mathematical/algorithmic ideas used in computation for problems in biology. They certainly provide plenty of step-by-step instructions via video and and text. However, I was able Read More
For someone like me with a background in computer science/engineering, this course had great content introducing biological concepts and the mathematical/algorithmic ideas used in computation for problems in biology. They certainly provide plenty of step-by-step instructions via video and and text. However, I was able to get a good grade (98%) without them checking for a deep enough understanding of the concepts & principles. Much of it felt like simply translating their pseudocode into your programming language of choice. I'll have to review everything if I ever get a job in bioinformatics...
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3 out of 4 people found the following review useful
2 years ago
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Anonymous completed this course.
A very good course that uses on online textbook, with built-in programming assignments using real biological data. I have a biology background, but limited programming experience. The assignments start off easy enough, but develop to more advanced algorithms that are explained somewhat vaguely, making the implementatio Read More
A very good course that uses on online textbook, with built-in programming assignments using real biological data. I have a biology background, but limited programming experience. The assignments start off easy enough, but develop to more advanced algorithms that are explained somewhat vaguely, making the implementation more challenging than it needed to be. I learnt alot though and will certainly be taking the next course in the series.
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2 out of 2 people found the following review useful
2 years ago
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Anonymous completed this course.
A very good course. It's a little difficult if you don't have a CS background, as the informatics part is a lot harder and counts more than the biology part. For me, it has been a great way to learn new things that I did not know and specially to discover a new exciting field.
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2 out of 2 people found the following review useful
a year ago
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Anonymous is taking this course right now.
Seems harder than it needs to be. Some of the instructions are very vague. Sometimes it is easier to come up with my own code than to follow their suggested code in many of the exercises,
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0 out of 2 people found the following review useful
2 years ago
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Anonymous completed this course.
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1 out of 1 people found the following review useful
2 years ago
Mariusz Bartosik completed this course, spending 10 hours a week on it and found the course difficulty to be medium.
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0 out of 1 people found the following review useful
2 years ago
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Stephen Mwema Nyakundi dropped this course.
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0 out of 1 people found the following review useful
2 years ago
Hary Mardhika is taking this course right now.
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1 out of 4 people found the following review useful
2 years ago
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Anonymous is taking this course right now.
I have PhD in bioinformatics (BSs in CS.). And I'm enjoying this course a lot! The algorithms are explained in very user-friendly way. So are the biological concepts. My big gratitutes to creators of the course content and the tools.
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2 years ago
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Anonymous completed this course.
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6 months ago
Ashlynn Pai completed this course.
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a year ago
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2 years ago
Preston Hinkel is taking this course right now.
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Ken Sellers completed this course.
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Halil Bilgin is taking this course right now.
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10 months ago
Chema Cortés partially completed this course.
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2 years ago
Daniel Fusca completed this course.
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