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#56, v5.0 Published:
#1247, v1.0 Published:

Title

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1Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence alignment in introductory undergraduate biology courses 1Bioinformatics: Investigating Sequence Similarity - A Plant Biology Approach

Authors

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1Sabrina Robertson (North Carolina State University) 1Ami Erickson ()
2Carlos Christopher Goller (North Carolina State University) 2Ami Erickson ()
3Steven Roof (Fairmont State University)   
4Benita Brink (Adams State University)   
5Adam Kleinschmit (Adams State University)   
6Hayley Orndorf (University of Pittsburgh)   

Description

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1<p>Introductory bioinformatics exercises often walk students through the use of computational tools, but often provide little understanding of what a computational tool does &quot;under the hood.&quot; 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.</p>  1<p style="margin:0in;margin-bottom:.0001pt"><o:p>&nbsp;</o:p></p>
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3<p>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.</p>  3<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;
   4font-family:Arial;color:black">This exercise was conducted in a sophomore level Plant and Fungal Biology course.&nbsp; I utilized most of exercise 1 and 2 from Adam Klenschmit&rsquo;s publication. To tailor the lab for a plant biology course I replaced the comparison in exercise 2 between the chimpanzee and human with two comparisons: one between Arabidopsis and a moss species; the other between Arabidopsis and yeast. I also removed the &ldquo;One Fish, Two Fish&rdquo; example to shorten the exercise.<o:p></o:p></span></p>
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5<p><strong>CourseSource Citation</strong></p>  6<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;
   7font-family:Arial;color:black"><o:p>&nbsp;</o:p></span></p>
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   9<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;
   10font-family:Arial;color:black">The goal for this activity was to demonstrate how bioinformatics is used to evaluate evolutionary relationships between plants.The week prior to completing this activity, students conducted a morphological comparison between bryophytes, vascular &ndash; seedless plants, angiosperms and gymnosperms. They had also read associated textbook chapters and discussed a paper about the evolution of land plants (de Vries and Archibald, 2018). <o:p></o:p></span></p>
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   12<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;
   13font-family:Arial;color:black"><o:p>&nbsp;</o:p></span></p>
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   15<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;
   16font-family:Arial;color:black">The activity was completed during a 3 hour lab session in a computer lab, and the activity was a little long for the time allotted.<o:p></o:p></span></p>
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   18<p><strong>CourseSource Citation of original publication</strong></p>
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7<p>Kleinschmit, A., Brink, B., Roof, S., Goller, C., and Robertson, S.D. &nbsp;2019. Sequence Similarity: An inquiry based and &ldquo;under the hood&rdquo; approach for incorporating molecular sequence alignment in introductory undergraduate biology courses. CourseSource. <a href="https://doi.org/10.24918/cs.2019.5">https://doi.org/10.24918/cs.2019.5</a></p> 20<p>Kleinschmit, A., Brink, B., Roof, S., Goller, C., and Robertson, S.D. &nbsp;2019. Sequence Similarity: An inquiry based and &ldquo;under the hood&rdquo; approach for incorporating molecular sequence alignment in introductory undergraduate biology courses. CourseSource. <a href="https://doi.org/10.24918/cs.2019.5">https://doi.org/10.24918/cs.2019.5</a></p> 

Quote

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1 1Plants may seem simple, but use ALL of your senses and "look" more closely.

Attachments

1 link — Sequence Similarity: An inquiry based and &quot;under the hood&quot; approach for incorporating molecular sequence alignment in introductory undergraduate biology courses | CourseSource 1 file — Bioinformatics Wkst_Plant Biology.docx
2 file — ./sequence_sim.JPG 2 file — Erickson_NIBLSEFMNTeachingNotes.docx
3 file — Exercise 2. Protein Alignment Hand Out.docx
4 link — Sequence Similarity: An inquiry based and &quot;under the hood&quot; approach for incorporating molecular sequence alignment in introductory undergraduate biology courses | CourseSource
5 file — publication_1264_1362/sequence_sim.JPG
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