Sequence Alignment with Affine Gap Penalties

Biological sequence alignment is the foundation of bioinformatics, but basic scoring systems often fail to represent real evolutionary events like insertions and deletions. This text-based course guides you from the fundamental principles of sequence comparison to implementing dynamic programming algorithms with affine gap penalties, giving you a realistic model for genomic data analysis. What you'll learn: - Understand the biological significance of insertions, deletions, and gap penalties in sequence alignment. - Differentiate between linear and affine gap penalty models. - Implement core alignment algorithms with affine gap penalties. - Write clean Python code with type hints to calculate alignment scores. - Analyze how changing gap open and extension parameters affects alignment outcomes. - Apply these scoring concepts to interpret modern genomic comparisons. You will start with core biological definitions and basic scoring matrices before moving step-by-step through the mathematics and logic of affine gap penalties, concluding with practical, written coding exercises. This course is perfect for beginners in bioinformatics, computer science students, or life scientists wanting to understand the algorithmic logic behind sequence comparison tools, with no prior advanced programming experience required. Start mastering the algorithms that power modern genomic analysis today.