Algorithmic Biology and Computational Genomics Fundamentals

Computational biology relies on efficient algorithms to decipher complex genomic data and solve modern biological challenges. This text-based course guides you through foundational concepts, terminology, and algorithmic principles essential for analyzing biological sequences and structures. You will explore the intersection of computer science and biology, learning how fundamental algorithmic paradigms address real-world genomic questions. The reading material begins with clear definitions of key terminology before progressing to practical problem-solving strategies and computational models. What you will learn: - Understand core biological terminology and data structures used in bioinformatics - Apply dynamic programming techniques for pairwise and multiple sequence alignment - Explore graph algorithms utilized in de novo genome assembly and fragment reconstruction - Analyze algorithms for phylogenetic tree construction and evolutionary modeling - Examine modern computational approaches to high-throughput sequencing data - Practice formulating biological questions as structured algorithmic problems The course begins with fundamental biological definitions and string manipulation basics, moves through standard alignment and assembly algorithms, and concludes with an exploration of open computational problems in modern genomics. This course is designed for beginners interested in bioinformatics, computer science students, and self-directed learners looking for a clear written introduction to algorithmic biology with no prior computational genomics experience required. Start reading to build a strong foundation in the algorithms shaping modern biological research.