Bioinformatics Foundations: Graphs and Genome Assembly

Reconstructing an entire genome from fragments of DNA is one of the most significant computational challenges in modern biology. This text-only course introduces you to the foundational graph theory concepts that make genome assembly possible. By reading through our structured lessons, you will transition from understanding basic mathematical graphs to analyzing how complex biological data is structured and resolved using algorithmic paths. You will gain the conceptual tools needed to understand how modern assemblers piece together genetic codes.\n\nWhat you'll learn:\n- Understand basic graph anatomy, including nodes, edges, directed paths, and cycles.\n- Explore the differences between Overlap-Layout-Consensus (OLC) and De Bruijn graph approaches.\n- Analyze how Eulerian and Hamiltonian paths are used to reconstruct DNA sequences.\n- Identify common assembly challenges such as genomic repeats, sequencing errors, and graph bubbles.\n- Learn how modern pangenome graphs represent genetic variation beyond a single reference genome.\n\nThe course begins with core definitions of graph theory before guiding you step-by-step through practical bioinformatics applications, sequence alignment concepts, and modern assembly algorithms. You will reinforce your reading with written conceptual exercises designed to test your understanding of algorithmic logic. This course is designed for beginner bioinformatics enthusiasts, biology students, and programmers looking to understand the intersection of computer science and genetics, with no prior background in advanced graph theory or biology required. Start exploring the mathematical structures that power modern genomic discovery today.