Algorithmic Biology Fundamentals: Sequence Analysis and Methods

Biological data is expanding rapidly, making computational algorithms essential for decoding genetic information and solving complex biological challenges. This course provides a clear, text-based introduction to the fundamental algorithms and computational techniques used in modern bioinformatics and algorithmic biology. You will begin by exploring essential terminology, biological data structures, and the foundational principles of sequence comparison. As you progress, you will read through step-by-step breakdowns of dynamic programming, graph theory applications, and search algorithms that drive contemporary computational biology. What you will learn: Understand foundational concepts and terminology in algorithmic biology and computational genetics; Apply dynamic programming algorithms for pairwise and multiple sequence alignment; Learn graph-based approaches such as de Bruijn graphs for genome assembly; Explore string indexing and pattern matching techniques for large-scale genomic datasets; Analyze phylogenetic models and tree-building algorithms for evolutionary studies; Discover modern computational approaches for high-throughput biological data. The course starts with basic definitions and structural concepts before advancing to algorithmic strategies for assembly and evolutionary modeling. This course is created for beginners, programmers, and science enthusiasts who want to understand computational biology without needing prior bioinformatics experience. Start reading today to build a strong foundation in algorithmic biology.