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Bioinformatics Algorithms
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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.

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Overview

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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.

Bioinformatics is an interdisciplinary field spanning diverse domains like biology, statistics, and computer science. It focuses...Show More

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

Familiarity with genomics

TAKEAWAY SKILLS

Python Programming

Scientific Algorithms

Content

105 Lessons3 Quizzes15 Challenges

Before Getting Started

1 Lessons

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

Introduction to the Course

Where in the Genome Does DNA Replication Begin?

20 Lessons

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

A Journey of a Thousand Miles

The Finding Origin of Replication Problem

DnaA Boxes

The Hidden Message Problem

Counting Words

Coding Challenge: Implement Pattern Count

The Frequent Words Problem

Some Hidden Messages are More Surprising than Others

Coding Challenge: Implement Pattern Matching

An Explosion of Hidden Messages

The Simplest Way to Replicate DNA

Asymmetry of Replication

Peculiar Statistics of the Forward and Reverse Half-Strands

Deamination

The Skew Diagram

Coding Challenge: Implement Minimum Skew

Some Hidden Messages are More Elusive than Others

A Final Attempt at Finding DnaA Boxes in E. coli

Epilogue: Complications in ori Predictions

Quiz

DNA Replication: Open Problems, Charging Stations, and Detours

17 Lessons

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

Open Problem: Multiple Replication Origins in a Bacterial Genome

Open Problem: Finding Replication Origins in Archaea

Open Problem: Finding Replication Origins in Yeast

Open Problem: Computing Probabilities of Patterns in a String

Charging Station: The Frequency Array

Charging Station: Conversions between Patterns and Numbers

Charging Station: Finding Frequent Words by Sorting

Charging Station: Solving the Clump Finding Problem

Charging Station: Solving Frequent Words with Mismatches Problem

Charging Station: Generating the Neighborhood of a String

Charging Station: Find Frequent Words with Mismatching by Sorting

Detour : Big-O Notation

Detour: Probabilities of Patterns in a String

Detour: The Most Beautiful Experiment in Biology

Detour: Directionality of DNA Strands

Detour: The Towers of Hanoi

Detour: The Overlapping Words Paradox

How Do We Assemble Genomes?

21 Lessons

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

Exploding Newspapers

The String Reconstruction Problem

String Reconstruction With Overlap Graph: From String To Graph

String Reconstruction With Overlap Graph: The Genome Vanishes

String Reconstruction with Overlap Graph: Graph Representation

String Reconstruction with Overlap Graph: Hamiltonian Paths

String Reconstruction with Gluing Nodes and De Bruijn Graphs

Walking in the de Bruijn Graph

De Bruijn Graphs: Another Way of Construction

De Bruijn Graphs: Construction from K-mer Composition

De Bruijn graphs: Comparison with Overlap Graphs

The Seven Bridges of Königsberg

Euler’s Theorem

Constructing Eulerian Cycles and Paths from Euler’s Theorem

Constructing Universal Strings

Assembling Genomes: From Reads to Read-Pairs

Assembling genomes: Transforming Read-Pairs to Long Virtual Reads

Assembling genomes: From Composition to Paired Composition

Assembling genomes: Paired De Bruijn Graphs

Epilogue: Genome Assembly Faces Real Sequencing Data

Quiz

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.

Charging Station: The Effect Of Gluing On the Adjacency Matrix

Charging Station: Generating All Eulerian Cycles

Charging Station: Reconstructing String in Paired De Bruijn Graph

Charging Station: Maximal Non-Branching Paths in a Graph

Detour: A Short History of DNA Sequencing Technologies

Detour: Repeats in the Human Genome

Detour: Graphs

Detour: The Icosian Game

Detour: Tractable and Intractable Problems

Detour: From Euler to Hamilton to de Bruijn

Detour: Pitfalls of Assembling Double-Stranded DNA

Detour: The BEST Theorem

How Do We Compare Biological Sequences?

27 Lessons

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

The Discovery of Antibiotics

How Do Bacteria Make Antibiotics?

Where is Tyrocidine Encoded in the Bacillus Brevis Genome?

Dodging the Central Dogma of Molecular Biology

Cracking the Non-Ribosomal Code

From Protein Comparison to Non-Ribosomal Code

What do Oncogenes and Growth Factors Have in Common?

Introduction to Sequence Alignment

Sequence Alignment and the Longest Common Subsequence

The Manhattan Tourist Problem

Sightseeing in an Arbitrary Directed Graph

Sequence Alignment is the Manhattan Tourist Problem in Disguise

Making a case for Dynamic Programming: The Change Problem

Changing Money Recursively

Changing Money Using Dynamic Programming

The Manhattan Tourist Problem Revisited

From Manhattan to an Arbitrary Directed Acyclic Graph

Backtracking in the Alignment Graph

Scoring Alignments

From Global to Local Alignment

The Changing Faces of Sequence Alignment

The Changing Faces of Sequence Alignment: Fitting Alignment

The Changing Faces of Sequence Alignment: Overlap Alignment

Penalizing Insertions and Deletions in Sequence Alignment

Space Efficient Sequence Alignment

Epilogue: Multiple Sequence Alignment

Quiz

Biological Sequences: Detours

6 Lessons

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

Detour: Fireflies and the Non-Ribosomal Code

Detour: Finding a Longest Common Subsequence

Detour: Constructing a Topological Ordering

Detour: PAM Scoring Matrices

Detour: Divide-and-Conquer Algorithms

Detour: Scoring Multiple Alignments

Conclusion

1 Lessons

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.

Course Author:

Phillip Compeau and

Pavel Pevzner

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