Genome Assembly Fundamentals: String Reconstruction with Overlap Graphs

How do scientists piece together millions of tiny DNA fragments to sequence an entire genome? Bioinformatics relies on elegant graph-based algorithms to solve this massive puzzle. This text-based course guides you through the foundational mathematics and computer science principles behind genome assembly. You will understand how to model DNA reads as nodes, identify overlapping sequences, and reconstruct original genomes using overlap graphs and modern algorithmic strategies. What you'll learn: Understand the core biological concepts of DNA sequencing reads, k-mers, and prefixes/suffixes; Construct overlap graphs by identifying matching sequence boundaries; Trace paths through graphs to reconstruct original strings from fragmented data; Compare overlap graphs with other modern assembly paradigms like de Bruijn graphs; Analyze the computational challenges of genome assembly, including repeats and sequencing errors; Practice algorithm design concepts using pseudocode and basic Python-style data structures. The course begins with essential biological and algorithmic terminology before guiding you step-by-step from simple string overlaps to complex graph traversal techniques. You will read clear explanations and study conceptual walkthroughs that demystify assembly pipelines. Designed for beginners in bioinformatics, computer science students, or biology enthusiasts, this course requires no prior experience in genomics or advanced graph theory. Start reading today to master the algorithmic foundation of modern genomics.