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Finding Hidden Messages in DNA (Bioinformatics I)

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HomeLife SciencesBioinformatics

Finding Hidden Messages in DNA (Bioinformatics I)

University of California, San Diego

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
University of California, San Diego

  • Pavel  Pevzner

    Taught by:  Pavel Pevzner, Professor

    Department of Computer Science and Engineering

  • Phillip Compeau

    Taught by:  Phillip Compeau, Visiting Researcher

    Department of Computer Science & Engineering
Basic Info
Course 1 of 7 in the Bioinformatics Specialization
LevelBeginner
Commitment4-10 hours/week
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.7 stars
Average User Rating 4.7See what learners said
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
  1. Video: (Check Out Our Wacky Course Intro Video)
  2. 읽기 자료: Course Details
  3. LTI 항목: 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. 읽기 자료: Week 1 FAQs (Optional)
  7. 읽기 자료: 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
  1. LTI 항목: 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. 읽기 자료: 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
  1. LTI 항목: 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. 읽기 자료: 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
  1. LTI 항목: 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. 읽기 자료: 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

    FAQs
    How It Works
    수업 활동
    수업 활동

    각 강좌는 대화형 교과서 형식으로 이루어지며, 사전 녹화된 비디오, 테스트, 프로젝트를 포함합니다.

    동료로부터의 도움
    동료로부터의 도움

    수천 명의 다른 동료 학습자와 함께 논의하고, 강좌 자료에 대하여 토론하고, 개념 습득을 위해 서로 도움을 받으십시오.

    수료증
    수료증

    귀하의 성과를 공식적으로 인정받아 친구, 동료, 회사에 성과를 공유해 보세요.

    Creators
    University of California, San Diego
    UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
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    Ratings and Reviews
    Rated 4.7 out of 5 of 309 ratings

    JL

    I couldn't finish successfully last question but I don't know why. I believe I understand the meaning of the question

    TS

    One of the best online courses I've ever taken. Since I come from a biotechnology background, this course was particularly relevant for me in terms of its depth and thoroughness. Seriously considering a future in computational biology, thanks to this course.

    Ivo Provazník

    Well prepared course although sometimes tough due to algorithmization tasks even for people with programming background.

    Nicolas Sebastian Vidal

    Insightful and introductory course to the bioinformatics world.



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