Machine Learning for Biomolecular and Ce

Introduction to machine learning techniques with applications to biological systems, emphasizing cell-biological molecular mechanisms and applications, and computational simulation. Overview of biology. Introduction to biological neurons and neural networks, learning and memory. Parallels between biological and artificial neural networks. Deep neural networks are introduced, hands-on computational experience for students. Big data from experiments or computational simulations: machine learning to extract mechanisms, dimensional reduction. Deep learning applications include drug discovery, protein structure prediction, molecular coarse-graining for simulations, and acceleration of molecular dynamics simulations.