Analyzing Biological Data with Graph Neural Networks

Course Description

This course will teach you how to use graph neural networks (GNNs) to analyze biological data. GNNs are a powerful machine learning model that can model and analyze complex relationships between data points. They are particularly well-suited for analyzing biological data, often represented as networks of interacting molecules, cells, or individuals.

In this course, you will learn the fundamentals of GNNs, including how they work, how to train them, and how to interpret their results. You will also learn about the different types of biological data that can be analyzed with GNNs and how to use GNNs to solve specific biological problems.

Course Objectives

Upon completion of this course, you will be able to:

• Understand the fundamentals of graph neural networks (GNNs)
• Train and evaluate GNNs for biological data analysis
• Apply GNNs to solve specific biological problems, such as protein structure prediction, drug discovery, and disease diagnosis.