Course Description

Foundational Discoveries in Genome Biology and Bioinformatics is based on close reading of key research articles in genome biology and bioinformatics. The format is interactive and requires students to contribute actively during class meetings. Groups of one to four students will be assigned to present context, figures, data, methods and impact from a number of research articles during the semester.  

This year’s course will focus on the protein folding problem and its “solution” in 2021 through AI/deep learning. Based on the readings, groups of one to four students will propose new applications of this technology. 

Readings may include research articles in the following areas: 

Background on predicting protein structure 

  1. Biophysics of protein folding 
  1. Homology modeling and threading 
  1. Correlated evolution 

AI, Deep Learning and AlphaFold2 

  1. Applications of AI and deep learning in biology 
  1. AlphaFold2 
  1. Other AI protein structure predictions  

Implications of accurate protein structure prediction 

  1. Databases of predicted structures 
  1. Protein-protein interaction predictions 
  1. Protein design 
  1. Drug screening 
  1. Effects of disease mutations 
  1. Structures in intrinsically disordered protein regions 



BCB330Y1 / BCH441H1 / MGY441H1 / CSB352H1 / CSB472H1 / EHJ352H1 / MGY428H1 or permission of the instructor 


Prof. A. Moses 

Contact Hours 


Required Text(s)/Readings 

Articles will be provided through Quercus. 

Evaluation (Subject to change) 

Participation and attendance
In class presentations
Writing assignments 




Last updated on June 13th, 2022