DNA Sequencing Algorithms and Python Implementations

Understanding the code of life requires powerful computational tools to process vast amounts of genetic information. This course bridges the gap between biology and computer science, showing you how to translate genomic puzzles into solvable algorithmic challenges. You will transition from a basic understanding of genetic data to building functional Python scripts that can align, index, and analyze complex sequences. * Understand the core biological concepts of DNA, genomics, and how sequencing technology generates data. * Implement string matching algorithms to locate specific patterns within massive genetic datasets. * Build and use indexing structures like the Burrows-Wheeler Transform for efficient sequence search. * Apply global and local alignment techniques to compare genetic sequences and identify variations. * Practice modern Python techniques including type hints and efficient memory management for large datasets. * Analyze real genomic data to solve practical problems in sequence assembly and mapping. The curriculum begins with foundational definitions of genomics and sequencing before progressing through the logic of read alignment and assembly. You will work through written explanations and code-based exercises designed to reinforce your understanding of bioinformatics workflows. This course is designed for beginners interested in the intersection of biology and software development, requiring no prior experience in bioinformatics. Start your journey into computational biology today.