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Developing a phylogram from computational resources.

Author(s): Melanie Lenahan1, Shea Cinquemani1

Raritan Valley Community College

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Summary:
This laboratory module, published on CourseSource, leads introductory biology students in the exploration of a basic set of bioinformatics concepts and tools.

Licensed under CC Attribution-NonCommercial-ShareAlike 4.0 International according to these terms

Version 1.0 - published on 01 Jun 2021 doi:10.25334/DP07-5Q37 - cite this

Adapted from: Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence alignment in introductory undergraduate biology courses v 5.0

Keywords

  1. phylogenetics
  2. bioinformatics
  3. sequencing
  4. FASTA
  5. NCBI
  6. NIBLSE
  7. algorithms
  8. BLAST
  9. multiple sequence alignment
  10. sequence similarity
  11. neighbor-joining distance matrix
  12. CourseSource
  13. phylogram
  14. percent identity matrix

Alignments

  1. Resource Type
  2. Audience Level
  3. Activity Length
  4. NIBLSE Core Competencies
  5. NIBLSE Status
Contents:
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Description

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 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.

CourseSource Citation

Kleinschmit, A., Brink, B., Roof, S., Goller, C., and Robertson, S.D.  2019. Sequence Similarity: An inquiry based and “under the hood” approach for incorporating molecular sequence alignment in introductory undergraduate biology courses. CourseSource. https://doi.org/10.24918/cs.2019.5

Notes

  • Exercise Format
    • This adaptation was piloted in a General Biology course and subsequently revised by a student from that class.  The purpose of the adaptation was to make the module more student friendly and cohesive.
  • Copy edits and text and activity choice modifications

Reference

Kleinschmit, A., Brink, B., Roof, S., Goller, C., and Robertson, S.D.  2019. Sequence Similarity: An inquiry based and “under the hood” approach for incorporating molecular sequence alignment in introductory undergraduate biology courses. CourseSource. https://doi.org/10.24918/cs.2019.5

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