Algorithmic Comparative Genomics and Evolutionary Biology

Next-generation sequencing has revolutionized our understanding of biology, challenging classical assumptions about how genomes evolve over time. This text-based course guides you through the computational algorithms and theoretical frameworks used to analyze complex evolutionary events and structural genomic variations. You will gain a solid understanding of how computational models resolve controversial genomic debates, from large-scale duplications to chromosomal rearrangements. What you'll learn: - Understand fundamental genomic terminology, sequencing principles, and evolutionary models - Analyze whole-genome duplication events using algorithmic methods - Examine the Random Breakage Model versus fragile breakage hypotheses in chromosome evolution - Explore computational reconstruction of ancestral mammalian genomes - Apply synteny block algorithms and genome rearrangement metrics - Evaluate modern high-throughput sequencing data through comparative genomics workflows The course begins with core biological and algorithmic definitions before progressing into comparative analysis techniques, rearrangement distance algorithms, and evolutionary reconstructions. Written explanations and code-focused algorithmic walkthroughs ensure concepts are easy to follow. This course is designed for curious beginners, programmers, and students interested in bioinformatics and computational biology. No advanced background in genetics is required to get started. Start reading today to discover how computational power unravels evolutionary history.