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Bioinformatics Algorithms

Bioinformatics Algorithms

Beginner

105 Lessons

10h

Certificate of Completion

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Explanations
Explanations

This course includes

24 Playgrounds
15 Challenges
176 Illustrations

This course includes

24 Playgrounds
15 Challenges
176 Illustrations
Course Overview
What You'll Learn
Course Content
How You'll Learn

Course Overview

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, an...Show More

TAKEAWAY SKILLS

Python Programming

Scientific Algorithms

What You'll Learn

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

Course Content

1

Before Getting Started

Introduction to the Course
2

Where in the Genome Does DNA Replication Begin?

A Journey of a Thousand MilesThe Finding Origin of Replication ProblemDnaA BoxesThe Hidden Message ProblemCounting Words
Coding Challenge: Implement Pattern CountThe Frequent Words ProblemSome Hidden Messages are More Surprising than OthersCoding Challenge: Implement Pattern MatchingAn Explosion of Hidden MessagesThe Simplest Way to Replicate DNAAsymmetry of ReplicationPeculiar Statistics of the Forward and Reverse Half-StrandsDeaminationThe Skew DiagramCoding Challenge: Implement Minimum SkewSome Hidden Messages are More Elusive than OthersA Final Attempt at Finding DnaA Boxes in E. coliEpilogue: Complications in ori PredictionsQuiz
3

DNA Replication: Open Problems, Charging Stations, and Detours

Open Problem: Multiple Replication Origins in a Bacterial GenomeOpen Problem: Finding Replication Origins in ArchaeaOpen Problem: Finding Replication Origins in YeastOpen Problem: Computing Probabilities of Patterns in a StringCharging Station: The Frequency ArrayCharging Station: Conversions between Patterns and NumbersCharging Station: Finding Frequent Words by SortingCharging Station: Solving the Clump Finding ProblemCharging Station: Solving Frequent Words with Mismatches ProblemCharging Station: Generating the Neighborhood of a StringCharging Station: Find Frequent Words with Mismatching by SortingDetour : Big-O NotationDetour: Probabilities of Patterns in a StringDetour: The Most Beautiful Experiment in BiologyDetour: Directionality of DNA StrandsDetour: The Towers of HanoiDetour: The Overlapping Words Paradox
4

How Do We Assemble Genomes?

Exploding NewspapersThe String Reconstruction ProblemString Reconstruction With Overlap Graph: From String To GraphString Reconstruction With Overlap Graph: The Genome VanishesString Reconstruction with Overlap Graph: Graph RepresentationString Reconstruction with Overlap Graph: Hamiltonian PathsString Reconstruction with Gluing Nodes and De Bruijn GraphsWalking in the de Bruijn GraphDe Bruijn Graphs: Another Way of ConstructionDe Bruijn Graphs: Construction from K-mer CompositionDe Bruijn graphs: Comparison with Overlap GraphsThe Seven Bridges of KönigsbergEuler’s TheoremConstructing Eulerian Cycles and Paths from Euler’s TheoremConstructing Universal StringsAssembling Genomes: From Reads to Read-PairsAssembling genomes: Transforming Read-Pairs to Long Virtual ReadsAssembling genomes: From Composition to Paired CompositionAssembling genomes: Paired De Bruijn GraphsEpilogue: Genome Assembly Faces Real Sequencing DataQuiz
5

Assemble Genomes: Charging Stations, and Detours

Charging Station: The Effect Of Gluing On the Adjacency MatrixCharging Station: Generating All Eulerian CyclesCharging Station: Reconstructing String in Paired De Bruijn GraphCharging Station: Maximal Non-Branching Paths in a GraphDetour: A Short History of DNA Sequencing TechnologiesDetour: Repeats in the Human GenomeDetour: GraphsDetour: The Icosian GameDetour: Tractable and Intractable ProblemsDetour: From Euler to Hamilton to de BruijnDetour: Pitfalls of Assembling Double-Stranded DNADetour: The BEST Theorem
6

How Do We Compare Biological Sequences?

27 Lessons

7

Biological Sequences: Detours

6 Lessons

8

Conclusion

1 Lesson

COURSE AUTHORS
Phillip Compeau and Pavel Pevzner

How You'll Learn

Hands-on Coding Environments

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