CSHL Comparative Genomics banner

Welcome to the 2023 Computational Genomics course! The primary focus of this course is the theory and practice of algorithms in computational biology, with the dual goals of using current methods more effectively for biological discovery and developing new algorithms. This page lists the daily schedule, helpful links, and instructor info. This information will be used throughout the course and updated frequently, so please bookmark this page.


Schedule


Group Photo

CSHL 2023 Computational Genomics


Instructors

David
David Hawkins, PhD

Associate Professor
University of Washington
Department of Genome Sciences

Lauren
Lauren Mills, PhD

Computational Biologist
University of Minnesota
Department of Pediatrics

Danny
Danny Miller, MD, PhD

Assistant Professor
University of Washington
Departments of Pediatrics and Laboratory Medicine & Pathology

William Pearson
William Pearson, PhD

Professor
University of Virginia
Department of Biochemistry and Molecular Genetics

Casey Gifford
Casey Gifford, PhD

Assistant Professor
Stanford University
Department of Pediatrics (Cardiology)

Stephanie Hicks
Stephanie Hicks, PhD

Associate Professor
Johns Hopkins
Department of Biostatistics

Aaron Quinlan
Aaron Quinlan, PhD

Professor
University of Utah
Departments of Human Genetics and Biomedical Informatics

Smita Krishnaswamy
Smita Krishnaswamy, PhD

Associate Professor
Yale University
Departments of Computer Science and Genetics

Erik Garrison
Erik Garrison, PhD

Assistant Professor
University of Tennessee
Department of Genetics, Genomics & Informatics

Nikhita
Nikhita Damaraju, MS

Predoctoral Scholar
University of Washington
Institute for Public Health Genetics

Sophie
Sophie Gibson

Predoctoral Scholar
University of Washington
Department of Genome Sciences

Name
Rachel Moss, MS

Predoctoral Scholar
University of Minnesota
Department of Pediatrics

Name
Andressa Oliveira de Lima, PhD

Postdoctoral Scholar
University of Washington
Department of Genome Sciences


Tutorials

Additional analysis tools via the Galaxy Training Network