Introductory bioinformatics exercises often walk students through the use of computational tools, but often provide little understanding of what a computational tool does "under the hood." A solid understanding of how a bioinformatics computational algorithm functions, including its limitations, is key for interpreting the output in a biologically relevant context. This introductory bioinformatics exercise integrates an introduction to web-based sequence alignment algorithms with models to facilitate student reflection and appreciation for how computational tools provide similarity output data. The exercise concludes with a set of inquiry-based questions in which students may apply computational tools to solve a real biological problem.

In the module, students first define sequence similarity and then investigate how similarity can be quantitatively compared between two similar length proteins using a Blocks Substitution Matrix (BLOSUM) scoring matrix. Students then look for local regions of similarity between a sequence query and subjects within a large database using Basic Local Alignment Search Tool (BLAST). Lastly, students access text-based FASTA-formatted sequence information via National Center for Biotechnology Information (NCBI) databases as they collect sequences for a multiple sequence alignment using Clustal Omega to generate a phylogram and evaluate evolutionary relationships. The combination of diverse, inquiry-based questions, paper models, and web-based computational resources provides students with a solid basis for more advanced bioinformatics topics and an appreciation for the importance of bioinformatics tools across the discipline of biology.