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bioinformatics_teaching_notes.md

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general considerations

  • an ideal bioinformatics course should contain the basic 'traditional' algorithms, along with new AI-based ones. AI-based algorithms are cool and modern and would drive the interest of students, who are likely also interested in opportunities outside academia
  • it should be hands-on, providing the students with code to build on for their studies;
  • it should put them in the condition to be able to modify the code and understand it
  • consider the language problem: should the course focus on R or python, or be code agnostic?

Syllabus

classical bioinformatics

  • genetics and genomics
  • structural bioinformatics and drug-discovery
  • database
  • AI
  • systems biology

outfields (biophysics, computational biophysics, inference, information theory)

useful articles/links

Texts

It's hard to find a "modern" text that includes AI-based algrithms; moreover, presenting AI tools would require a general introduction to machine learning tools

group links

course syllabi