Resources: Compare
#56, v4.0
#1317, v1.0
Title
| Old Version | New Version | ||
|---|---|---|---|
| 1 | Bioinformatics - Investigating Sequence Similarity | 1 | Sequence Similarity in Developmental Biology - A Bioinformatics Exercise Using Myostatin |
Authors
| Old Version | New Version | ||
|---|---|---|---|
| 1 | Adam Kleinschmit (Adams State University) | 1 | Barbara Murdoch () |
| 2 | Benita Brink (Adams State University) | 2 | Barbara Murdoch () |
| 3 | Steven Roof (Fairmont State University) | ||
| 4 | Komal Vig (Alabama State University) | ||
| 5 | Carlos Christopher Goller (North Carolina State University) | ||
| 6 | Sabrina Robertson (North Carolina State University) | ||
| 7 | Hayley Orndorf (University of Pittsburgh) | ||
| 8 | Benita Brink (Adams State University) | ||
Description
| Old Version | New Version | ||
|---|---|---|---|
| 1 | <p>The following modules are from a pre-print version of the "Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence alignment in introductory undergraduate biology courses" learning resource accepted for publication in CourseSource, which is currently in press.</p> | 1 | <p>This exercise integrates bioinformatics with developmental biology, and provides an introduction regarding how to use bioinformatics to assess sequence similarities. The implications of these similarities provides students with a basic understanding of how model organisms can provide useful information regarding human health and disease.</p> |
| 2 | |||
| 3 | <p>This laboratory module, leads introductory biology students in the exploration of a basic set of bioinformatics concepts and tools. The exercise utilizes simple paper models to help students understand matrices and algorithms prior to use of web-based computational tools. Students start the module by defining sequence similarity and then investigating how similarity can be quantitatively compared between two similar length proteins using a BLOSUM scoring matrix. Students then consider finding local regions of similarity between a sequence query and subjects within a large database using BLAST. Lastly, students practice accessing FASTA formatted sequence information via NCBI databases as they collect sequences for a multiple sequence alignment in order to generate a phylogenetic tree.</p> | ||
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Attachments
| 1 | file — ./Updated version 4 files_11_21_18/S1. student_handout.docx | 1 | file — 1.Murdoch_NIBLSEFMNTeachingNotesTemplateSp19.docx |
|---|---|---|---|
| 2 | file — ./Updated version 4 files_11_21_18/S10. Zika_seqs_student.txt | 2 | file — 2. Student handout_Murdoch_Similarity in Developmental Biology.docx |
| 3 | file — ./Updated version 4 files_11_21_18/S11. Vet_Med_seqs.txt | 3 | file — 3. S3. BLAST_handout_Kleinschmit et al.docx |
| 4 | file — ./Updated version 4 files_11_21_18/S2. instructor_solutions.docx | 4 | file — 4. TGF-b signaling pathway.pptx |
| 5 | file — ./Updated version 4 files_11_21_18/S3. BLAST_handout.docx | 5 | file — 5. Bioinformatics_BIO 434 WORKSHEET_vfinal2.docx |
| 6 | file — ./Updated version 4 files_11_21_18/S4. MSA_handout.docx | 6 | file — 5.1. Bioinformatics_BIO 434 WORKSHEET answers_vfinal2.docx |
| 7 | file — ./Updated version 4 files_11_21_18/S5. neighbor_Joining_handout.docx | 7 | link — Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence alignment in introductory undergraduate biology courses | CourseSource |
| 8 | file — ./Updated version 4 files_11_21_18/S6. Cytochrome_C_seqs.txt | ||
| 9 | file — ./Updated version 4 files_11_21_18/S7. ADH2_seqs_instructor.txt | ||
| 10 | file — ./Updated version 4 files_11_21_18/S8. ADH2_seqs_student.txt | ||
| 11 | file — ./Updated version 4 files_11_21_18/S9. Zika_seqs_instructor.txt | ||
| 12 | file — ./sequence_sim.JPG |