Bioinformatics Algorithms: Solving the String Reconstruction Problem

Reassembling a genome from millions of tiny DNA fragments is one of the most significant computational challenges in modern biology. This text-based course guides you through the fundamental algorithms and mathematical models used to solve the string reconstruction problem. You will transition from understanding basic DNA string representations to analyzing the core graph-based algorithms that power modern genome assemblers, equipping you with the foundational bioinformatics skills needed to conceptualize genomic data structures. What you'll learn: Understand the biological and computational foundations of genome assembly; Define k-mer compositions and analyze how genomes are broken down into overlapping substrings; Construct and traverse overlap graphs to reconstruct original strings; Explore De Bruijn graphs and Eulerian paths as scalable solutions for genomic data; Compare modern sequencing paradigms, including short-read and long-read computational challenges; Practice algorithmic thinking by tracing reconstruction steps through written walkthroughs. The course begins with essential terminology and the mathematical formulation of k-mers, then progresses systematically from simple overlap alignments to advanced graph-based assembly paradigms. Designed for beginners in bioinformatics, computer science students, or biology enthusiasts, this course requires no prior experience in genome assembly. Start reading today to master the algorithmic logic behind genomic discovery.