Description: Explore the cutting-edge intersection of artificial intelligence (AI) and structural biology in this minicourse. As machine learning continues to advance at an unprecedented pace, the fields of biology and computational science are converging to revolutionize our understanding of the molecular basis of life. In this course, we will explore cutting-edge powerful AI-driven tools to predict complex protein structures, interactions and more. The class will combine lectures, hands-on exercises, and real-world case studies. You will learn the power and limitations of current methods, and how they could be used to advance your research.
Structure: The course will be a mixture of formal lectures, guided practical exercises and a personal project to be presented at the end of the course.
Outcome: The students who successfully complete the course will be able to use the state-of-the-art tools in AI-assisted protein structure prediction and design, to inform hypotheses in their research, validate predictions, plan experiments, and understand the extended uses and limitations of these tools in their field.
Grading: Students are expected to attend all classes and actively participate in discussions and hands-on activities (25%). During the course, the students will identify a protein modeling question and solve it using the tools examined in class. At the end of the course, they will submit a research report describing the question, rationale for experimental design, and present an analysis and interpretation of results in a biological context (75%).