Finding Hidden Messages in DNA
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About the Book
Finding Hidden Messages in DNA represents the first two chapters of Bioinformatics Algorithms: an Active Learning Approach, which is one of the first textbooks to emerge from the recent Massive Open Online Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors’ acclaimed MOOC on Coursera, this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of both biology and computer science.
The two chapters cover two central biological questions: “Where in the Genome Does Replication Begin?” and “Which DNA Patterns Play the Role of Molecular Clocks?” The textbook then steadily develops the algorithmic sophistication required to answer each question. Dozens of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on the Rosalind Bioinformatics Textbook Track.
The textbook website augments the textbook by providing additional educational materials, including video lectures and PowerPoint slides.
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About the Authors
Active Learning Publishers
Phillip Compeau
Dr. Compeau is the Assistant Department Head and an Associate Teaching Professor in the Computational Biology Department at Carnegie Mellon University. He directs the undergraduate program and serves as an assistant director for the MS in Computational Biology program, and co-founded (with Josh Kangas) the PreCollege Program in Computational Biology, the first educational program in computational biology for high school students in the United States.
Dr. Compeau also teaches a variety of courses, and he is passionate about how online and offline educational materials can inform and enrich each other as we build an effective 21st Century classroom. He completed a Ph.D. in mathematics at UC San Diego, where he co-founded Rosalind, a platform for learning computational biology and algorithms through problem solving that has reached over 300,000 users. Phillip also helped lead the development of the first massive open online course (MOOC) in computational biology in 2013, which has since grown into the Bioinformatics Specialization on Coursera. He is the co-author (with Pavel Pevzner) of Bioinformatics Algorithms: An Active Learning Approach, a bestselling textbook in computational biology that has been adopted by 200 instructors in over 40 countries. And he is the founder of the Biological Modeling open online course project.
Episode 227
An Interview with Phillip Compeau
Pavel Pevzner
Pavel Pevzner (http://cseweb.ucsd.edu/~ppevzner/) is Professor of Computer Science and Engineering at University of California San Diego (UCSD), where he holds the Ronald R. Taylor Chair and has taught a Bioinformatics Algorithms course for the last 12 years. In 2006, he was named a Howard Hughes Medical Institute Professor. In 2011, he founded the Algorithmic Biology Laboratory in St. Petersburg, Russia, which develops online bioinformatics platform Rosalind (http://rosalind.info). His research concerns the creation of bioinformatics algorithms for analyzing genome rearrangements, DNA sequencing, and computational proteomics. He authored Computational Molecular Biology (The MIT Press, 2000), co-authored (jointly with Neil Jones) An Introduction to Bioinformatics Algorithms (The MIT Press, 2004), and Bioinformatics Algorithms: An Active Learning Approach (Active Learning Publishers, 2014). For his research, he has been named a Fellow of both the Association for Computing Machinery (ACM) and the International Society for Computational Biology (ISCB).
Contents
Table of Contents
A Journey of a Thousand Miles
Hidden Messages in the Replication Origin
DnaA boxes
Hidden messages in "The Gold-Bug"
Counting words
The Frequent Words Problem
Frequent words in Vibrio cholerae
Some Hidden Messages are More Surprising than Others
An Explosion of Hidden Messages
Looking for hidden messages in multiple geomes
The Clump Finding Problem
The Simplest Way to Replicate DNA
Asymmetry of Replication
Peculiar Statistics of the Forward and Reverse Half-Strands
Deamination
The skew diagram
Some Hidden Messages are More Elusive than Others
A Final Attempt at Finding DnaA Boxes in E. coli
Epilogue: Complications in oriC Predictions
Open Problems
Multiple replication origins in a bacterial genome
Finding replication origins in archaea
Finding replication origins in yeast
Computing probabilities of patterns in a string
Charging Stations
The frequency array
Converting patterns to numbers and vice-versa
Finding frequent words by sorting
Solving the Clump Finding Problem
Solving the Frequent Words with Mismatches Problem
Generating the neighborhood of a string
Finding frequent words with mismatches by sorting
Detours
Big-O notation
Probabilities of patterns in a string
The most beautiful experiment in biology
Directionality of DNA strands
The Towers of Hanoi
The overlapping words paradox
Bibliography Notes
Chapter 2: Which DNA Patterns Play the Role of Molecular Clocks?Do We Have a "Clock" Gene?
Motif Finding is More Difficult than You Think
Identifying the evening element
Hide and seek with motifs
A brute force algorithm for motif finding
Scoring Motifs
From motifs to profile matrices and consensus strings
Towards a more adequate motif scoring function
Entropy and the motif logo
From Motif Finding to Finding a Median String
The Motif Finding Problem
Reformulating the Motif Finding Problem
The Median String Problem
Why have we reformulated the Motif Finding Problem?
Greedy Motif Search
Using the profile matrix to roll dice
Analyzing greedy motif finding
Motif Finding Meets Oliver Cromwell
What is the probability that the sun will not rise tomorrow?
Laplace's Rule of Succession
An improved greedy motif search
Randomized Motif Search
Rolling dice to find motifs
Why randomized motif search works
How Can a Randomized Algorithm Perform So Well?
Gibbs Sampling
Gibbs Sampling in Action
Epilogue: How Does Tuberculosis Hibernate to Hide from Antibiotics?
Charging Stations
Solving the Median String Problem
Detours
Gene expression
Dna arrays
Buffon's needle
Complications in motif finding
Relative entropy
Bibliography Notes
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