Finding Hidden Messages in DNA (Bioinformatics I)

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Beschrijving

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About this course: 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 rol…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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.

Who is this class for: This course is primarily aimed at undergraduate-level learners in computer science, biology, or a related field who are interested in learning about how the intersection of these two disciplines represents an important frontier in modern science.

Created by:  University of California, San Diego
  • Taught by:  Pavel Pevzner, Professor

    Department of Computer Science and Engineering
  • Taught by:  Phillip Compeau, Visiting Researcher

    Department of Computer Science & Engineering
Basic Info Course 1 of 7 in the Bioinformatics Specialization Level Beginner Commitment 4-10 hours/week Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.7 stars Average User Rating 4.7See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Syllabus


WEEK 1


Week 1: Welcome!



<p>Welcome to class!</p><p>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:</p><ol><li>Weeks 1-2: Where in the Genome Does DNA Replication Begin? (<em>Algorithmic Warmup</em>)</li><li>Weeks 3-4: Which DNA Patterns Play the Role of Molecular Clocks? (<em>Randomized Algorithms</em>)</li></ol><p>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.</p><p>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 <a href="http://bioinformaticsalgorithms.com" target="_blank">print companion</a>. 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!</p><p><img src="http://bioinformaticsalgorithms.com/images/cover/replication_cropped.jpg" title="Image: http://bioinformaticsalgorithms.com/images/cover/chapter1_cropped.jpg" width="500"></p><p><a href="http://compeau.cbd.cmu.edu" target="_blank"><img src="http://bioinformaticsalgorithms.com/images/Compeau_caricature.jpg" width ="150"></a> <a href="http://cseweb.ucsd.edu/~ppevzner/" target="_blank"><img src="http://bioinformaticsalgorithms.com/images/Pevzner_caricature.jpg" width ="150"></a></p><p>Phillip and Pavel</p>


3 videos, 3 readings expand


  1. Video: (Check Out Our Wacky Course Intro Video)
  2. Reading: Course Details
  3. LTI Item: Stepik Interactive Text for Week 1
  4. Video: Where in the Genome Does DNA Replication Begin? (Part 1) (11:37)
  5. Video: Where in the Genome Does DNA Replication Begin? (Part 2) (06:24)
  6. Reading: Week 1 FAQs (Optional)
  7. Reading: What is Pseudocode? (Optional)

Graded: Week 1 Quiz
Graded: Open in order to Sync Your Progress: Stepik Interactive Text for Week 1

WEEK 2


Week 2: Finding Replication Origins



<p>Welcome to Week 2 of class!</p> <p>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.</p>


2 videos, 1 reading expand


  1. LTI Item: Stepik Interactive Text for Week 2
  2. Video: Where in the Genome Does DNA Replication Begin? (Part 3) (09:05)
  3. Video: Where in the Genome Does DNA Replication Begin? (Part 4) (04:10)
  4. Reading: Week 2 FAQs (Optional)

Graded: Week 2 Quiz
Graded: Open in order to Sync Your Progress: Stepik Interactive Text for Week 2

WEEK 3


Week 3: Hunting for Regulatory Motifs



<p>Welcome to Week 3 of class!</p> <p>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. &nbsp;What does a late night casino trip with two 18th Century French mathematicians have in common with finding molecular clocks? &nbsp;Start learning to find out...</p> <p><img src="https://d396qusza40orc.cloudfront.net/bioinformatics%2Fimages%2Fchapter3_final.jpg" title="Image: https://d396qusza40orc.cloudfront.net/bioinformatics%2Fimages%2Fchapter3_final.jpg" width="528"></p>


3 videos, 1 reading expand


  1. LTI Item: Stepik Interactive Text for Week 3
  2. Video: From Implanted Patterns to Regulatory Motifs (Part 1) (10:09)
  3. Video: From Implanted Patterns to Regulatory Motifs (Part 2) (05:06)
  4. Video: From Implanted Patterns to Regulatory Motifs (Part 3) (07:22)
  5. Reading: Week 3 FAQs (Optional)

Graded: Week 3 Quiz
Graded: Open in order to Sync Your Progress: Stepik Interactive Text for Week 3

WEEK 4


Week 4: How Rolling Dice Helps Us Find Regulatory Motifs
<p>Welcome to Week 4 of class!</p> <p>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.</p>


3 videos, 1 reading expand


  1. LTI Item: Stepik Interactive Text for Week 4
  2. Video: How Rolling Dice Helps Us Find Regulatory Motifs (Part 1) (12:43)
  3. Video: How Rolling Dice Helps Us Find Regulatory Motifs (Part 2) (05:37)
  4. Video: How Rolling Dice Helps Us Find Regulatory Motifs (Part 3) (07:46)
  5. Reading: Week 4 FAQs (Optional)

Graded: Week 4 Quiz
Graded: Open in order to Sync Your Progress: Stepik Interactive Text for Week 4

WEEK 5


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.




    Graded: Bioinformatics Application Challenge

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