Bioinformatics Algorithms: String Reconstruction with Overlap Graphs

How do scientists piece together millions of tiny DNA fragments into a complete genome? Understanding the algorithmic foundations of string reconstruction is the key to unlocking computational biology. This text-only course guides you through the core mathematical and algorithmic concepts used in genome assembly, transitioning from basic string definitions to building overlap graphs and mapping Hamiltonian paths. What you'll learn: - Understand the fundamental terminology of sequence alignment and string reconstruction. - Build and analyze overlap graphs using simulated DNA reads. - Apply Hamiltonian path algorithms to solve the shortest common superstring problem. - Compare overlap-layout-consensus approaches with modern de Bruijn graph methods. - Evaluate the computational complexity and limitations of Hamiltonian paths in genome assembly. The course begins with essential definitions of strings and k-mers before diving into graph theory foundations and practical algorithmic walkthroughs. It is designed for beginners in computer science or biology who want to understand the intersection of algorithms and genetics, with no prior bioinformatics experience required. Start reading today to master the algorithmic logic behind genome sequencing.