Sequence Alignment and the Manhattan Tourist Problem

How do scientists compare DNA sequences to find evolutionary relationships? The secret lies in a classic grid-navigation puzzle known as the Manhattan Tourist Problem. This text-only course demystifies computational biology by showing you how to transform biological questions into mathematical graphs. You will learn how to write dynamic programming algorithms to solve sequence alignment problems efficiently. What you'll learn: 1. Understand the foundational terminology of bioinformatics, DNA sequencing, and evolutionary mutations. 2. Learn how the Manhattan Tourist Problem models sequence alignment using directed acyclic graphs. 3. Apply dynamic programming techniques to find optimal paths through grid-based networks. 4. Implement sequence alignment algorithms conceptually and through clean, modern code snippets. 5. Practice analyzing the time and space complexity of alignment algorithms to ensure efficiency. The course begins with core terminology and graph theory basics before guiding you through constructing alignment matrices and writing your first dynamic programming solutions. This course is designed for beginners in computer science or biology who want to explore the intersection of both fields, with no prior advanced math or bioinformatics experience required. Start reading today to unlock the algorithmic foundation of modern computational biology.