Machine Learning in Genomics - Fall 2019
Dive into the world of computational biology with this comprehensive lecture series from MIT. Explore key topics in machine learning and genomics, including dynamic programming, hidden Markov models, RNA analysis, epigenomics, regulatory genomics, network inference, deep learning, population genetics, genome-wide association studies, comparative genomics, phylogenetics, single-cell genomics, cancer genomics, and genome engineering. Learn essential techniques for data analysis, clustering, and classification in genomics research. Gain insights into presenting scientific papers, creating effective figures, and delivering impactful presentations. Master the buzzwords and concepts that drive cutting-edge research in computational biology and genomics.