Genome Assembly Algorithms with Paired De Bruijn Graphs

Reconstructing an entire genome from billions of tiny, fragmented DNA reads is one of the most significant computational challenges in modern biology. This text-based course introduces you to the core algorithmic concepts behind genome assembly, focusing on how paired-end reads solve the repeat resolution problem. By understanding how biological data is translated into mathematical structures, you will gain a clear perspective on how modern assemblers map the code of life. You will build a solid theoretical foundation in graph theory as applied to bioinformatics, transitioning from basic sequence concepts to advanced graph traversal techniques. Through clear written explanations, you will learn how to model genomic data and resolve structural ambiguities that arise during sequencing. What you'll learn: - Understand the foundational concepts of k-mers, DNA sequencing reads, and the limitations of single-end sequencing. - Construct De Bruijn graphs from sequence data and represent overlapping k-mers computationally. - Apply Eulerian path and cycle algorithms to reconstruct original genomic sequences. - Solve the repeat problem in genome assembly using paired De Bruijn graphs and read-pairs. - Explore modern hybrid assembly concepts that combine short-read graph techniques with long-read sequencing data. The course begins with essential biological and algorithmic terminology before guiding you step-by-step through graph construction, pathfinding, and sequence reconstruction. You will consolidate your learning through written algorithmic walkthroughs and conceptual text-based exercises. This course is designed for beginners in bioinformatics, computer science students, or biology enthusiasts seeking to understand the math behind sequence assembly. No prior background in advanced graph theory or biology is required. Start reading today to unlock the algorithmic secrets of genomic sequencing.