Comparing Genes, Proteins, and Genomes: Bioinformatics III
Master advanced sequence alignment and genome comparison techniques. Learn dynamic programming and combinatorial algorithms for biological sequence analysis.
Master advanced sequence alignment and genome comparison techniques. Learn dynamic programming and combinatorial algorithms for biological sequence analysis.
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.
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پښتو, বাংলা, اردو, 3 more
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What you'll learn
Master sequence alignment algorithms for DNA and protein analysis
Apply dynamic programming to biological sequence comparison
Understand genome rearrangements and evolutionary patterns
Identify fragile regions in genomic structures
Use BLAST and other bioinformatics tools effectively
Analyze multiple sequence alignments
Skills you'll gain
This course includes:
2.17 Hours PreRecorded video
5 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This comprehensive course explores the comparison of genes, proteins, and entire genomes using advanced computational methods. The first half focuses on comparing short biological sequences using dynamic programming for determining mutations between genes/proteins. The second half addresses genome-wide comparisons, examining large-scale mutations and genome rearrangements. Students learn to use key bioinformatics tools like BLAST and study evolutionary patterns in genome organization, including the identification of fragile regions in the human genome.
Introduction to Sequence Alignment
Module 1 · 4 Hours to complete
From Finding a Longest Path to Aligning DNA Strings
Module 2 · 2 Hours to complete
Advanced Topics in Sequence Alignment
Module 3 · 3 Hours to complete
Genome Rearrangements and Fragility
Module 4 · 4 Hours to complete
Applying Genome Rearrangement Analysis to Find Genome Fragility
Module 5 · 3 Hours to complete
Bioinformatics Application Challenge
Module 6 · 3 Hours to complete
Fee Structure
Instructors
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"
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.
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