Functional Interpretation of High-Throughput Data

In this course, students will learn how to interpret high-throughput ‘omic data, including DNA-sequencing, transcriptomics, epigenomics, proteomic, metabolomics, microbiome, imaging, and CRISPR-Cas9 screening data. They become acquainted with basic paradigms of functional genomic annotation, including gene / transcript / protein definition, noncoding regulatory annotations, protein-protein interaction networks, and flux balance models. They will gain familiarity the application of commonly used statistical inference, machine learning, exploratory data analysis, and data visualization paradigms to the analysis of high throughput data in relevant areas of cancer biology, epigenetics, population genetics, precision medicine.