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Finding Mutations in DNA and Proteins (Bioinformatics VI)

This course is part of Bioinformatics Specialization.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Bioinformatics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.7

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English

پښتو, বাংলা, اردو, 3 more

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Finding Mutations in DNA and Proteins (Bioinformatics VI)

This course includes

23 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Implement efficient DNA read mapping algorithms

  • Master the Burrows-Wheeler transform for pattern matching

  • Develop solutions for inexact pattern matching

  • Apply hidden Markov models to sequence analysis

  • Analyze highly mutated protein sequences

  • Use profile HMMs for protein classification

Skills you'll gain

DNA Sequencing
Pattern Matching
Hidden Markov Models
Protein Analysis
Burrows-Wheeler Transform
Sequence Alignment
Mutation Detection
Bioinformatics Algorithms
HIV Analysis

This course includes:

2.5 Hours PreRecorded video

3 assignments, 1 peer review

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

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There are 6 modules in this course

This advanced bioinformatics course focuses on computational methods for finding mutations in DNA and proteins. The first half covers efficient algorithms for mapping DNA fragments to reference genomes using combinatorial pattern matching and the Burrows-Wheeler transform. The second half explores hidden Markov models for identifying protein functions, particularly in rapidly mutating sequences like HIV. Students learn both theoretical foundations and practical applications of these advanced bioinformatics tools.

Introduction to Read Mapping

Module 1 · 4 Hours to complete

The Burrows-Wheeler Transform

Module 2 · 4 Hours to complete

Speeding Up Burrows-Wheeler Read Mapping

Module 3 · 3 Hours to complete

Introduction to Hidden Markov Models

Module 4 · 3 Hours to complete

Profile HMMs for Sequence Alignment

Module 5 · 4 Hours to complete

Bioinformatics Application Challenge

Module 6 · 3 Hours to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Bioinformatics Specialization

Instructors

Pavel Pevzner
Pavel Pevzner

8,33,777 Students

16 Courses

Pioneering Bioinformatics Scholar and Computational Biology Innovator

Pavel Arkadevich Pevzner serves as the Ronald R. Taylor Professor of Computer Science at the University of California, San Diego, and director of the NIH Center for Computational Mass Spectrometry, where he has revolutionized the field of computational biology since 2000. After receiving his Ph.D. in mathematics and physics from the Moscow Institute of Physics and Technology, he completed postdoctoral work with Michael Waterman at USC, before establishing himself through positions at Penn State and USC. His groundbreaking research spans bioinformatics algorithms, genome rearrangements, DNA sequencing, and computational proteomics, leading to significant advances in genome assembly and antibiotics discovery. His academic excellence has been recognized through numerous prestigious honors, including the Howard Hughes Medical Institute Professorship (2006), ACM Fellowship (2010), ISCB Fellowship (2012), and the ACM Paris Kanellakis Theory and Practice Award (2018). As an educator, he has transformed bioinformatics education through innovative approaches, including the development of massive open online courses that have reached over half a million students, and authored influential textbooks including "Computational Molecular Biology: An Algorithmic Approach" and "Bioinformatics Algorithms: An Active Learning Approach"

Phillip Compeau
Phillip Compeau

4.1 rating

282 Reviews

2,88,261 Students

8 Courses

Computational Biology Educator and Educational Innovation Pioneer

Phillip Compeau is an Assistant Teaching Professor in the Carnegie Mellon University Computational Biology Department, where he serves as Assistant Director of the Master's in Computational Biology program. He holds a Ph.D. in mathematics from UC San Diego and completed his Master's degree at Cambridge University. Phillip co-founded Rosalind, an online platform for learning bioinformatics. A retired tennis player, he dreams of one day going pro in golf.

Finding Mutations in DNA and Proteins (Bioinformatics VI)

This course includes

23 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.