#  Protein Structure Prediction: Harnessing AlphaFold/ColabFold 

 





 Semester:   Spring 

|

 Year offered:  2023 

|

 Link: [Course Website](https://hms.az1.qualtrics.com/jfe/form/SV_8qsDsdLp10oZ0sm) 

 

 

 

 **Course Description**  
  
AlphaFold represents a dramatic increase in the power of AI systems to predict a protein’s 3D structure from its amino acid sequence. This nanocourse will introduce how predictive models like Alphafold/Collab work, their strengths and limitations, and how to interpret their predictive results.  
  
This is a hands-on workshop; participants will use Alphafold and ColabFold, submit computing jobs to the O2 computing platform, and visualize 3D structures. No prior computational experience is required – the workshop will introduce participants to machine learning and the command-line environment.

 **Instructors: Ogie Avramovska, *Curriculum Fellow in Genetics and Genomics*, and Chris Magnano, *Curriculum Fellow in the Center for Computational Biomedicine*  
**Guest Lecturer: Sergey Ovchinnikov (John Harvard Distinguished Science Fellow)  
**Technical Support: Alex Truong and Calvin Cox (Research Computing)  
**Milestone Criteria:** Attendance at all 3 sessions and in-class submission of nanocourse reflection in session 3  
  
**[CLICK HERE TO REGISTER](https://hms.az1.qualtrics.com/jfe/form/SV_8qsDsdLp10oZ0sm)**

 **SESSION 1 - Wednesday, March 22nd, 3:30 - 5:30, TMEC 250**   
(Limited to 50)  
  
**SESSION 2 - Monday, March 27th, 3:30 - 5:30, TMEC 333**  
(Limited to 24 - Hands-on Session)  
  
**SESSION 3 - Wednesday, March 29th, 3:30 - 5:30, TMEC 338**  
(Limited to 24 - Hands-on Session)