Bioinformatics Algorithms: Solving Genetic Mysteries with Code

How do scientists locate the origin of a disease, map the human genome, or find evolutionary links between species? The answer lies in bioinformatics—the intersection of biology and computer science that powers modern genomic research. This text-only course guides you through the fundamental algorithms used to solve complex biological puzzles. You will transition from understanding basic DNA structure to reading and writing computational solutions that analyze genetic sequences, assemble genomes, and identify evolutionary relationships. What you'll learn: - Understand the fundamental biological terms and computational concepts that bridge computer science and genetics. - Analyze DNA sequences to find replication origins and regulatory patterns using string matching algorithms. - Reconstruct genomes from short DNA reads using graph theory and assembly algorithms. - Align genetic sequences to measure evolutionary distances using dynamic programming. - Utilize modern Python data structures and libraries to handle real-world genomic data formats. You will start with foundational definitions of DNA, RNA, and basic algorithmic complexity before progressing to sequence alignment, genome assembly, and evolutionary tree construction. Each concept is reinforced with step-by-step written explanations and clear code examples. This course is designed for aspiring bioinformaticians, software developers curious about biology, and life sciences students wanting to learn programming. No advanced background in biology or computer science is required. Begin your journey into the code that drives modern genetic discovery today.