DNA Sequence Analysis: Coding a Pattern Count Algorithm

Bioinformatics sits at the intersection of biology and computer science, where analyzing massive genomic datasets requires efficient, precise code. If you want to understand how scientists locate specific gene sequences, identify evolutionary patterns, or detect mutations, mastering pattern-counting algorithms is the perfect starting point. In this course, you will progress from understanding core genomic concepts to writing and testing your own pattern-matching algorithm. You will learn how to represent DNA sequences in code, implement search logic step-by-step, and apply modern development standards to ensure your solution is robust and readable. What you'll learn: Understand foundational bioinformatics concepts, including DNA strings, nucleotides, and k-mers; Implement a robust pattern-counting algorithm using modern Python syntax and type hints; Analyze the time and space complexity of your algorithm to understand its performance limits; Write automated tests using pytest to verify your code against various edge cases; Apply your code to genomic datasets to find specific sequence motifs. This text-based course begins with essential biological and algorithmic terminology before leading you through the step-by-step development of your pattern-matching program, complete with clear code walkthroughs and written exercises. Designed for aspiring bioinformatics analysts and programmers new to computational biology, this course requires only basic programming familiarity and no prior genetics background. Start coding your first genomic analysis tool today.