Finding Hidden Messages in DNA (Bioinformatics I)

开始时间: 04/22/2022 持续时间: Unknown

所在平台: CourseraArchive 课程类别: 计算机科学 大学或机构: University of California, San Diego （加州大学圣地亚哥分校） 授课老师： Phillip E. C. Compeau Pavel Pevzner

课程主页: https://www.coursera.org/course/hiddenmessages

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课程详情

A genome may look like an incomprehensible string of the letters A, C, G, and T. Yet hidden in the three billion nucleotides of your genome is a secret language. This course offers an introduction to how we can start to understand this language by using algorithms to find hidden messages in DNA.

What do these hidden messages say?  In the first chapter of the course, hidden DNA messages indicate where a bacterium starts replicating its genome, a problem with applications in bioengineering and beyond. In the second chapter, hidden DNA messages tell us how organisms know whether it is day or night as well as how the bacterium causing tuberculosis is able to hide from antibiotics. We will see how randomized algorithms, which toss coins and roll dice, can be used to find these messages.

Each of the two central topics in the course builds the algorithmic knowledge required to address this challenge. Along the way, coding challenges and exercises, many of which ask you to apply your skills to real genetic data, will be directly integrated into the text at the exact moment they are needed.

课程大纲

Where in the Genome Does Replication Begin? (Algorithmic Warmup):

• Introduction to DNA replication
• Hidden messages in the replication origin
• Some hidden messages are more surprising than others
• An explosion of hidden messages
• The simplest way to replicate DNA
• Asymmetry of replication
• Peculiar statistics of the forward and reverse half-strands
• Some hidden messages are more elusive than others
• A final attempt at finding DnaA boxes in E. coli
• Epilogue: Complications in oriC predictions

Which DNA Patterns Play the Role of Molecular Clocks? (Randomized Algorithms)

• Do we have a "clock" gene?
• Motif finding is more difficult than you think
• Scoring motifs
• From motif finding to finding a median string
• Greedy motif search
• Motif finding meets Oliver Cromwell
• Randomized motif search
• How can a randomized algorithm perform so well?
• Gibbs sampling
• Gibbs sampling in action
• Complications in motif finding
• Epilogue: How does Tuberculosis hibernate to hide from antibiotics?

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