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Pavel Pevzner and Phillip Compeau

You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome?

Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read short pieces of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces. We will further learn about brute force algorithms and apply them to sequencing mini-proteins called antibiotics.

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You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome?

Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read short pieces of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces. We will further learn about brute force algorithms and apply them to sequencing mini-proteins called antibiotics.

In the first half of the course, we will see that biologists cannot read the 3 billion nucleotides of a human genome as you would read a book from beginning to end. However, they can read shorter fragments of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces in what amounts to the largest jigsaw puzzle ever put together.

In the second half of the course, we will discuss antibiotics, a topic of great relevance as antimicrobial-resistant bacteria like MRSA are on the rise. You know antibiotics as drugs, but on the molecular level they are short mini-proteins that have been engineered by bacteria to kill their enemies. Determining the sequence of amino acids making up one of these antibiotics is an important research problem, and one that is similar to that of sequencing a genome by assembling tiny fragments of DNA. We will see how brute force algorithms that try every possible solution are able to identify naturally occurring antibiotics so that they can be synthesized in a lab.

Finally, you will learn how to apply popular bioinformatics software tools to sequence the genome of a deadly Staphylococcus bacterium that has acquired antibiotics resistance.

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What's inside

Syllabus

Week 1: Introduction to Genome Sequencing

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: How Do We Assemble Genomes? (Graph Algorithms)
  2. How Do We Sequence Antibiotics? (Brute Force Algorithms)

Each of the two chapters of content in the class is accompanied by a Bioinformatics Cartoon created by talented San Diego artist 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 time machine trip to 1735, a stack of newspapers, a jigsaw puzzle, and a giant ant invading a riverside city have to do with putting together a genome? Start learning today to find out!

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Week 2: Applying Euler's Theorem to Assemble Genomes

Welcome to Week 2 of class!

This week in class, we will see how a 300 year-old mathematical theorem will help us assemble a genome from millions of tiny pieces of DNA.

Week 3: Sequencing Antibiotics

Welcome to Week 3 of class!

This week, we begin a new chapter, titled "How Do We Sequence Antibiotics?"  In this chapter, we will learn how to determine the amino acid sequences making up antibiotics using brute force algorithms.

Below is this week's Bioinformatics Cartoon.

Week 4: From Ideal to Real Spectra for Antibiotics Sequencing

Welcome to Week 4 of class!

Last week, we discussed how to sequence an antibiotic peptide from an ideal spectrum. This week, we will see how to develop more sophisticated algorithms for antibiotic peptide sequencing that are able to handle spectra with many false and missing masses.

Week 5: Bioinformatics Application Challenge!
Welcome to Week 5 of class! This week, we will see how to apply genome assembly tools to sequencing data from a dangerous pathogenic bacterium.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by Pavel Pevzner, Phillip Compeau, who are recognized for their work in bioinformatics
Examines genome sequencing, which is highly relevant to modern medicine
Develops algorithmic approaches to genome sequencing and antibiotic sequencing, which are core skills for bioinformatics
Provides opportunities to apply bioinformatics software to real-world data
Requires students to have some background in biology and computer science

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Reviews summary

Genome sequencing: engaging course with challenging assignments

Learners say this course offers engaging assignments and a great introduction to Genome sequencing. It is highly recommended for those with a strong interest in Bioinformatics, but be prepared for difficult exams and a significant time commitment. Despite some frustrations with difficult algorithms and occasional lack of instructor responsiveness, learners appreciate the excellent course outline and challenging quizzes that force them to learn. Overall, this course is a great resource for those seeking to expand their knowledge in Genome sequencing.
Exercises are challenging and force learners to understand concepts.
"The exercises were challenging."
"The programming assignments really make you learn."
"It helped me a great deal in understanding and using various data structures."
Instructors may not respond to questions or provide timely feedback.
"The course, although good, seems to be abandoned as there were no responses from teaching staff for months, and several students were stuck on final assignment for weeks."
This course requires a significant time commitment of 20-30 hours per week.
"The course is great, but be prepared to spend 20-30 hours a week on it..."
Exams and quizzes are challenging and require a strong understanding of the material.
"The quizzes are very challenging."
"Pretty solid course, with tough algorithms to crack."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Genome Sequencing (Bioinformatics II) with these activities:
Read 'Algorithms on Strings, Trees, and Sequences'
This book provides a comprehensive overview of algorithms used in genome sequencing.
Show steps
  • Read the first few chapters
  • Focus on chapters relevant to genome sequencing
  • Take notes and solve practice problems
Review molecular biology concepts
Strong molecular biology knowledge is essential for understanding genome sequencing.
Browse courses on Molecular Biology
Show steps
  • Read textbook chapters
  • Watch online videos
  • Take practice quizzes
Solve practice problems on Euler's Theorem
Solving practice problems on Euler's Theorem will help you master this important concept used in genome sequencing.
Show steps
  • Review Euler's Theorem
  • Solve problems of increasing difficulty
Four other activities
Expand to see all activities and additional details
Show all seven activities
Write a blog post about the importance of gene sequencing
Writing about gene sequencing will reinforce your understanding of the topic and help others learn about its importance.
Show steps
  • Research the topic
  • Outline the blog post
  • Write the first draft
  • Edit and revise the blog post
Solve 20 Euler's Theorem problems
Euler's Theorem will help you understand key concepts of graph theory used in genome sequencing.
Show steps
  • Review Euler's Theorem
  • Assemble sequences of length 3
  • Solve sequences of increasing length
Assemble 10 short DNA fragments from a given genome
Practicing genome assembly will improve your understanding of the challenges involved and the techniques used.
Show steps
  • Obtain the DNA fragments
  • Assemble the fragments using a graph algorithm
  • Verify the assembled genome
Analyze 10 real-world antibiotic peptide spectra
Analyzing real-world antibiotic peptide spectra will expose you to the challenges of antibiotic sequencing and help you develop practical skills.
Show steps
  • Obtain the spectra
  • Identify peaks and determine mass-to-charge ratios
  • Use software to sequence the peptides
  • Verify the sequences using databases

Career center

Learners who complete Genome Sequencing (Bioinformatics II) will develop knowledge and skills that may be useful to these careers:
Computational Biologist
Computational Biologists use computational tools to analyze biological data. This can include developing algorithms for genome assembly or for sequencing antibiotics. A course in genome sequencing would be very helpful to a Computational Biologist who wants to specialize in genomics.
Professor
Professors teach and conduct research in colleges and universities. This can include teaching and conducting research in the field of genomics. A course in genome sequencing would be very helpful to a Professor who wants to teach or conduct research in genomics.
Research Scientist
Research Scientists conduct experiments to investigate and analyze the nature and properties of living organisms and their environments. They do this using a variety of techniques including genome sequencing and analysis. A course in genome sequencing could be very helpful to a Research Scientist, especially one who wants to concentrate on genomics.
Geneticist
Geneticists study genes and heredity. This can include using genome sequencing to identify genetic disorders or to develop new treatments for genetic diseases. A course in genome sequencing would be very helpful to a Geneticist who wants to specialize in genomics.
Medical Researcher
Medical Researchers conduct experiments to investigate the causes and treatments of diseases. This can include using genome sequencing to identify genetic risk factors for disease or to develop new treatments for genetic diseases. A course in genome sequencing could be very helpful to a Medical Researcher who wants to specialize in genomics.
Biostatistician
A Biostatistician applies statistical methods to a variety of medical and health care problems. This could include analyzing data from genetic or genomic studies. Knowledge of genome sequencing can be very helpful for a Biostatistician who works in this field.
Pharmaceutical Scientist
Pharmaceutical Scientists develop and test new drugs and treatments for diseases. This can include using genome sequencing to identify new drug targets or to develop personalized treatments for genetic diseases. A course in genome sequencing could be very helpful to a Pharmaceutical Scientist who wants to specialize in genomics.
Clinical Laboratory Scientist
Clinical Laboratory Scientists analyze body fluids or tissues to provide information about the health of a patient. This can include using genome sequencing to identify genetic disorders or to develop personalized treatment plans. A course in genome sequencing could be very helpful to a Clinical Laboratory Scientist who wants to specialize in genomics.
Data Scientist
Data Scientists use data to solve problems and make decisions. This can include using genome sequencing data to identify genetic risk factors for disease or to develop new drugs. A course in genome sequencing could be very helpful to a Data Scientist who wants to specialize in genomics.
Epidemiologist
Epidemiologists investigate the causes of disease and other health problems in populations. This can include using genome sequencing to identify genetic risk factors for disease or to track the spread of infectious diseases. A course in genome sequencing could be very helpful to an Epidemiologist who wants to specialize in genomics.
Science Writer
Science Writers communicate scientific information to the public. This can include writing about genome sequencing and its applications. A course in genome sequencing could be very helpful to a Science Writer who wants to specialize in genomics.
Forensic Scientist
Forensic Scientists collect and analyze evidence to help solve crimes. This can include using genome sequencing to identify suspects or to determine the cause of death. A course in genome sequencing could be very helpful to a Forensic Scientist who wants to specialize in forensic genomics.
Quality Control Analyst
Quality Control Analysts ensure that products and services meet quality standards. This can include using genome sequencing to ensure the quality of food or drugs. A course in genome sequencing could be very helpful to a Quality Control Analyst who wants to specialize in genomics.
Healthcare Consultant
Healthcare Consultants help healthcare organizations improve their efficiency and effectiveness. This can include using genome sequencing to identify genetic risk factors for disease or to develop new treatments for genetic diseases. A course in genome sequencing could be very helpful to a Healthcare Consultant who wants to specialize in genomics.
Physician
Physicians diagnose and treat diseases and injuries. This can include using genome sequencing to identify genetic risk factors for disease or to develop personalized treatments for genetic diseases. A course in genome sequencing could be very helpful to a Physician who wants to specialize in genomics.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Genome Sequencing (Bioinformatics II).
This textbook by the instructor of this course provides a rigorous introduction to the algorithms used in computational molecular biology, including those used in genome sequencing and assembly.
Provides a comprehensive overview of bioinformatics, covering topics related to genome sequencing and assembly, and providing both theoretical and practical aspects.
This textbook provides a broad overview of bioinformatics, introducing the fundamental concepts and techniques used in the field, including genome sequencing and assembly.
Provides a comprehensive overview of DNA sequencing protocols and technologies, providing a background for the concepts covered in this course.
Provides an up-to-date overview of next-generation sequencing technologies and their applications, which can help students understand the latest advancements in the field beyond the scope of this course.
Provides an introduction to the R programming language and the Bioconductor package, which are widely used for bioinformatics analysis.

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