Predictive Modeling, Structure Predictions and AI in Biomedical Research.

Catalog description

Permission of instructor -- Knowledge of introductory biochemistry and molecular biology is required -- Previous experiences with R, PyMol, and machine learning are NOT necessary for attending this class. This is an introductory course for biomedical graduate students and scientists focused on the use of machine learning/big data exploration to solve relevant research questions. The course will include: (a) Principles of machine learning in biomedical research (b) Introduction of supervised machine learning approach (c) Big data analysis, RNAseq and Olink proteomics, and (d) Prediction of protein structures using a machine learning approach, and evaluation and analysis of the predicted protein structures. This course will include a large codebase using R in machine learning and introduce state-of-the-art packages in machine learning. The instructors will use real biomedical research cases.