Workshop on AI Algorithms for Structural Biology
Workshop (Bioinformatics/CS Undergraduates), Tel Aviv University, School of Computer Science, 2023
Summary
Proteins form the molecular basis of all life, and yet, we lack reliable means to predict what they do, how they do it, where and when. Indeed, although their primary constituents - amino acids - are well-characterized, the size and diversity of proteins make physical simulations of their behavior extremely challenging. To overcome these challenges, Machine learning approaches have become increasingly popular since the 90’s for predicting how proteins fold, recognize one another and function. While initially only moderately successful, deep learning has enabled radical progress across tasks, culminating with the celebrated AlphaFold algorithm for protein structure prediction in 2021. This workshop is a joint introduction to machine learning and structural biology, with an emphasis on practical tools and current research topics. Prior knowledge of either domain is desirable but not necessary. In the first part of the semester, we will cover key concepts including protein structures & folding, supervised learning and deep learning. Then, we will discuss the biological and algorithm concepts underlying AlphaFold. The second part of the semester will be dedicated to group research projects related to the topic. Evaluation will be based on the project reports and presentations. The course will be in English.
Syllabus
- Week 1: Introduction to proteins and machine learning.
- Week 2: Visual analysis of protein structures.
- Week 3: Quantitative analysis of protein structures.
- Week 4: Supervised machine learning (I)
- Week 5: Supervised machine learning (II)
- Week 6: Convolutional & Graph neural networks
- Week 7: Project kickstart meetings
- Weeks 8-12: Project meetings
- Week 13: Oral presentation