Finding Mutations in DNA and Proteins (Bioinformatics VI) from Coursera

In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins.

In the first half of the course, we would like to ask how an individual's genome differs from the "reference genome" of the species. Our goal is to take small fragments of DNA from the individual and "map" them to the reference genome. We will see that the combinatorial pattern matching algorithms solving this problem are elegant and extremely efficient, requiring a surprisingly small amount of runtime and memory.

In the second half of the course, we will learn how to identify the function of a protein even if it has been bombarded by so many mutations compared to similar proteins with known functions that it has become barely recognizable. This is the case, for example, in HIV studies, since the virus often mutates so quickly that researchers can struggle to study it. The approach we will use is based on a powerful machine learning tool called a hidden Markov model.

Finally, you will learn how to apply popular bioinformatics software tools applying hidden Markov models to compare a protein against a related family of proteins.

What's inside

Syllabus

Week 1: Introduction to Read Mapping

Welcome to our class! We are glad that you decided to join us.

In this class, we will consider the following two central biological questions (the computational approaches needed to solve them are shown in parentheses):

How Do We Locate Disease-Causing Mutations? (Combinatorial Pattern Matching)
Why Have Biologists Still Not Developed an HIV Vaccine? (Hidden Markov Models)

As in previous courses, each of these two chapters is accompanied by a Bioinformatics Cartoon created by talented 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.

Image: https://stepic.org/media/attachments/lessons/292/chapter7_cropped.jpg

Week 2: The Burrows-Wheeler Transform

Welcome to week 2 of the class!

This week, we will introduce a paradigm called the Burrows-Wheeler transform; after seeing how it can be used in string compression, we will demonstrate that it is also the foundation of modern read-mapping algorithms.

Week 3: Speeding Up Burrows-Wheeler Read Mapping

Welcome to week 3 of class!

Last week, we saw how the Burrows-Wheeler transform could be applied to multiple pattern matching. This week, we will speed up our algorithm and generalize it to the case that patterns have errors, which models the biological problem of mapping reads with errors to a reference genome.

Week 4: Introduction to Hidden Markov Models

Welcome to week 4 of class!

This week, we will start examining the case of aligning sequences with many mutations -- such as related genes from different HIV strains -- and see that our problem formulation for sequence alignment is not adequate for highly diverged sequences.

To improve our algorithms, we will introduce a machine-learning paradigm called a hidden Markov model and see how dynamic programming helps us answer questions about these models.

Week 5: Profile HMMs for Sequence Alignment

Welcome to week 5 of class!

Last week, we introduced hidden Markov models. This week, we will see how hidden Markov models can be applied to sequence alignment with a profile HMM. We will then consider some advanced topics in this area, which are related to advanced methods that we considered in a previous course for clustering.

Week 6: Bioinformatics Application Challenge

Welcome to the sixth and final week of class!

This week brings our Application Challenge, in which we apply the HMM sequence alignment algorithms that we have developed.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Strengthens an existing foundation for intermediate learners in bioinformatics

Develops advanced knowledge, specifically in mutation detection using hidden Markov models and pattern matching

Led by Pavel Pevzner and Phillip Compeau, respected researchers and instructors in bioinformatics

Provides hands-on instruction through bioinformatics software tools, such as those focused on hidden Markov models

Teaches combinatorial pattern matching algorithms for mapping DNA fragments to a reference genome

Reviews summary

Compelling course on mutations in dna and proteins

Learners say this course is engaging, well-structured, and a favorite in its specialization. They especially enjoyed learning about suffix trees, BWT, pattern matching, and HMMs. Overall, students describe this course as both great and helpful.

Engaging topics include suffix trees, BWT, pattern matching, and HMMs.

"Really loved learning about suffix trees/arrays, BWT, Pattern matching, HMMs!"

Content is well-organized and helpful.

"The contents were so well organized and helpful to develop a proper insight"

Course is a favorite among students.

"It was probably my favorite in this specialization (at least, out of first six)."

"It was the greatest course I've ever attended."

Course may be less engaging than others in the specialization.

"I did this course after the course "Algorithms for DNA Sequencing" of Ben Langmead. Since Ben Langmead was excellent in his explanations, my expectations were the same for this course but I felt that it is not as good as Ben Langmead course maybe because there are no practical videos about programming ideas."

Career center

Learners who complete Finding Mutations in DNA and Proteins (Bioinformatics VI) will develop knowledge and skills that may be useful to these careers:

Professor

A Professor teaches and conducts research in a specific field. This course will provide you with the skills to develop and teach courses in bioinformatics, a key skill for any Professor. The course will cover topics such as bioinformatics algorithms and applications, which are essential topics for any Professor teaching in the field of bioinformatics.

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Research Scientist

A Research Scientist conducts research in a specific field. This course will provide you with the skills to develop and conduct research in bioinformatics, a key skill for any Research Scientist. The course will cover topics such as bioinformatics algorithms and applications, which are essential topics for any Research Scientist working in the field of bioinformatics.

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Systems Biologist

A Systems Biologist studies the complex interactions between molecules in living organisms. This course will provide you with the skills to understand the systems-level properties of biological systems, a key skill for any Systems Biologist. The course will cover topics such as network analysis and systems biology modeling, which are essential topics for any Systems Biologist working in the field of bioinformatics.

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Computational Biologist

A Computational Biologist uses mathematical and computational techniques to solve biological problems. This course will provide you with the skills to develop and apply computational methods to solve biological problems, a key skill for any Computational Biologist. The course will cover topics such as sequence alignment and protein structure prediction, which are essential topics for any Computational Biologist working in the field of bioinformatics.

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Technical Writer

A Technical Writer writes technical documentation. This course will provide you with the skills to write technical documentation for bioinformatics software and applications, a key skill for any Technical Writer. The course will cover topics such as technical writing and documentation, which are essential topics for any Technical Writer working in the field of bioinformatics.

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Biostatistician

A Biostatistician analyzes and interprets large biological datasets to answer complex biological questions. This course will provide you with the skills to analyze and interpret data, a key skill for any Biostatistician. The course will cover topics such as statistical methods for analyzing DNA and protein sequences, which are essential topics for any Biostatistician working in the field of bioinformatics.

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Teacher

A Teacher teaches students in a specific subject. This course will provide you with the skills to develop and teach courses in bioinformatics, a key skill for any Teacher. The course will cover topics such as bioinformatics algorithms and applications, which are essential topics for any Teacher teaching in the field of bioinformatics.

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Geneticist

A Geneticist studies the genes and heredity of organisms. This course will provide you with the skills to understand the genetic basis of diseases, a key skill for any Geneticist. The course will cover topics such as DNA sequencing and genome analysis, which are essential topics for any Geneticist working in the field of bioinformatics.

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Molecular Biologist

A Molecular Biologist studies the structure and function of molecules in living organisms. This course will provide you with the skills to understand the molecular basis of diseases, a key skill for any Molecular Biologist. The course will cover topics such as protein structure and function, which are essential topics for any Molecular Biologist working in the field of bioinformatics.

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Statistician

A Statistician collects, analyzes, and interprets data. This course will provide you with the skills to analyze and interpret data, a key skill for any Statistician. The course will cover topics such as statistical methods for analyzing DNA and protein sequences, which are essential topics for any Statistician working in the field of bioinformatics.

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Software Engineer

A Software Engineer designs, develops, and maintains software systems. This course will provide you with the skills to develop software tools for bioinformatics, a key skill for any Software Engineer. The course will cover topics such as software design and development, which are essential topics for any Software Engineer working in the field of bioinformatics.

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Web Developer

A Web Developer designs and develops websites. This course will provide you with the skills to develop web applications for bioinformatics, a key skill for any Web Developer. The course will cover topics such as web design and development, which are essential topics for any Web Developer working in the field of bioinformatics.

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Pharmacist

A Pharmacist dispenses and advises on the use of medications. This course will provide you with the skills to understand the molecular basis of drugs, a key skill for any Pharmacist. The course will cover topics such as drug metabolism and pharmacokinetics, which are essential topics for any Pharmacist working in the field of bioinformatics.

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Physician

A Physician diagnoses and treats diseases. This course will provide you with the skills to understand the molecular basis of diseases, a key skill for any Physician. The course will cover topics such as disease genomics and personalized medicine, which are essential topics for any Physician working in the field of bioinformatics.

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Data Scientist

A Data Scientist uses data to solve business problems. This course will provide you with the skills to collect, clean, and analyze data, a key skill for any Data Scientist. The course will cover topics such as machine learning and statistical modeling, which are essential topics for any Data Scientist working in the field of bioinformatics.

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