Sequence Alignment in Bioinformatics: Global and Local Methods

Bioinformatics relies on comparing DNA, RNA, and protein sequences to uncover evolutionary history and biological functions. This written course guides you through the foundational concepts of sequence alignment, helping you confidently choose and apply the right algorithms to biological data. What you'll learn: 1. Understand the fundamental differences between global and local sequence alignment. 2. Apply scoring matrices like PAM and BLOSUM to evaluate sequence similarity. 3. Trace the steps of the Needleman-Wunsch and Smith-Waterman algorithms through clear written explanations. 4. Analyze biological sequences using modern tools and Python-based libraries like Biopython. 5. Evaluate alignment scores and interpret the biological significance of conserved regions. You will start with essential biological terminology and scoring concepts before walking through algorithmic steps and modern computational implementations. Designed for beginners in life sciences or programming, this course requires no prior background in bioinformatics. Start your journey into computational biology and master the math behind gene comparison.