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Bioinformatics Algorithms

Gain insights into bioinformatics by exploring genome assembly, DNA replication, and genetic sequence comparison through algorithmic principles. Delve into real-world applications like vaccine development and climate change.

5.0

105 Lessons

10h

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LEARNING OBJECTIVES

Familiarity with genomics
Awareness of open problems in the field
Hands-on experience coding bioinformatics algorithms
Ability to apply a diverse set of graph, path-finding, and subsequence-matching algorithms to biological data

Learning Roadmap

105 Lessons3 Quizzes15 Challenges

Before Getting Started

Get familiar with the intersection of biological challenges and algorithmic concepts.

Introduction to the Course

Where in the Genome Does DNA Replication Begin?

Grasp the complexities of DNA replication origins, computational challenges, and algorithmic solutions.

DNA Replication: Open Problems, Charging Stations, and Detours

17 Lessons

Explore unresolved problems in DNA replication and advanced algorithmic techniques in bioinformatics.

How Do We Assemble Genomes?

21 Lessons

Grasp the fundamentals of genome assembly, from short DNA reads to de Bruijn graphs.

Assemble Genomes: Charging Stations, and Detours

12 Lessons

Take a closer look at genome assembly, Eulerian cycles, paired De Bruijn graphs, and DNA sequencing history.

How Do We Compare Biological Sequences?

27 Lessons

See how it works to compare biological sequences using various alignment techniques.

Biological Sequences: Detours

6 Lessons

Piece together the parts of biological sequences and computational techniques in bioinformatics.

Conclusion

Learn how to use bioinformatics tools, from DNA replication origins to machine learning.

Final Remarks

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

ABOUT THIS COURSE

Bioinformatics is an interdisciplinary field spanning diverse domains like biology, statistics, and computer science. It focuses on developing algorithms that extract useful information from biological data. These insights help address critical issues like waste cleanup, vaccine development, and climate change. This course focuses on algorithmic principles driving advances in bioinformatics. It starts by introducing the learner to important concepts in genomics, such as DNA replication, genome assembly, and comparing genetic sequences. It applies concepts from algorithm design to genomics, like Eulerian paths, de Bruijn graphs, and longest common subsequences. It includes coding challenges, as well as sections on additional insights and thought-provoking questions. By the end of this course, you’ll have a basic knowledge of genomics. You’ll be able to apply a diverse set of algorithms to biological data to get insights and also be introduced to various open problems in this field.

ABOUT THE AUTHOR

Phillip Compeau

Serial online education founder and professor at Carnegie Mellon University

Learn more about Phillip

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