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Functional Interpretation of High-Throughput Data

Functional Interpretation of High- (CMPB 5005 03)
Credits: 4
Course Directors: Marcin Imielinski, MD, PhD, and Jan Krumsiek, PhD

Course Description

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.

Course Schedule

1-2 lectures per week. Midterm proposal and final data science project. A number of faculty members from WMC, MSKCC, and broader NYC genomics community will give lectures within their research areas

Semester: Spring
Time: Wednesdays 1:30-3:30pm
Location: BB 1401

Course Syllabus

TBA

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Weill Cornell Medicine Graduate School of Medical Sciences 1300 York Ave. Box 65 New York, NY 10065 Phone: (212) 746-6565 Fax: (212) 746-5981