Algorithmic Biology and Computational Genomics Fundamentals

Modern biology relies heavily on computational algorithms to decipher complex genomic data and model biological systems. This text-based course introduces you to the core algorithmic concepts behind sequence analysis, genome assembly, and phylogenetic reconstruction through structured reading and written problem-solving. You will begin with essential biological terminology and fundamental computer science principles before exploring the classic and contemporary algorithms that drive modern bioinformatics. By examining how biological challenges translate into computational problems, you will gain a clear understanding of sequence alignment, graph theory in assembly, and statistical modeling in biology. What you'll learn: - Understand foundational biological concepts, genomic data structures, and standard terminology - Master dynamic programming algorithms for local and global sequence alignment - Apply graph algorithms, including de Bruijn and overlap graphs, to genome assembly problems - Explore computational methods for constructing and evaluating phylogenetic trees - Analyze modern high-throughput sequencing data paradigms and pattern-matching strategies - Practice algorithmic thinking by working through written computational biology exercises The curriculum progresses smoothly from key definitions and mathematical foundations to algorithmic designs and modern biological problem-solving. This course is designed for beginners in bioinformatics, computer science students, and life science researchers seeking a solid algorithmic grounding without prior advanced computational experience. Start reading today to build your algorithmic biology foundation.