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Build Multiomic and Visualization Skills in Bioscience Lecture

Author(s): Xyanthine Parillon

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Summary:
This resource promotes inclusive learning by using all free platforms to extend the central dogma to an applied experience. Genomics is focused on with literature reviews that are performed to identify genes implicated in a clinical condition.…

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This resource promotes inclusive learning by using all free platforms to extend the central dogma to an applied experience. Genomics is focused on with literature reviews that are performed to identify genes implicated in a clinical condition. Transcriptomics with data mining of RNAseq acquisition is followed by protein sequence acquisition and modeling. Teaching and learning of communication in the process of science is the final focus.

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

Version 1.0 - published on 19 Nov 2022 doi:10.25334/CMJD-WF17 - cite this

Keywords

  1. genetics
  2. Biochemistry
  3. Biology and Biochemistry Eduation
  4. Protein Structure
  5. Bioinformatics and Genomics
  6. Functional Genomics
  7. transcriptomics
  8. proteomics
  9. RNAseq
  10. Clinical genomics
  11. protein structure modeling
  12. Inclusive teaching
  13. 3D protein structure /function analysis
  14. inclusive classrooms
  15. 3D protein structures
  16. inclusive
  17. gene

Alignments

  1. Resource Type
  2. Audience Level
  3. Activity Length
  4. Inclusive Pedagogy for Life Science Education
  5. QUBES Universal Design Tagging Ontology
  6. Open Science and Education Practices Ontology
Contents:
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Description

Personalized learning can be adopted by having each student pick a gene or the class can work on one gene. Trancripts of RNA expression will be mined in NCBI to determine RNAsequencing annotations. One can teach and learn how to acquire FASTA protein sequences and create 3D models with potential protein analysis. This activity will give you a opportunity to teach and learn how to communicate results with figures and create figure legends. The resource examples are centered around biomedical results. However, the same activies could be applied to plant and animal studies. 

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