Short Course on the Genetics of Addiction

About

Millions of people worldwide struggle with addiction, a chronic, complex condition involving genes, environment, and behavior. To provide a path toward deeper understanding and improved public health measures, scientists must first unlock the fundamental biology of the disorder. This requires advanced genetic tools and methods to reveal the genes and biological networks that contribute to addiction.

This JAX short course brings together world-renowned experts in addiction, human genetics, and mouse genetics. Through a combination of lectures and hands-on computational modules, the course will feature:

• New methods and applications of mouse genetics to addiction,
• Genetic and bioinformatics approaches to augment behavioral studies, and
• Techniques for analyzing human genetic studies of addiction.

The course also provides key opportunities to network with students, researchers, and other professionals; and explore potential scientific collaborations.

Genetics of Addiction is geared toward students of all experience levels, from undergraduate and graduate students who seek an introduction to the field, to experienced addiction researchers who wish to hone their genetic skills and knowledge. Course attendees are invited to bring their own data for analysis during the hands-on laboratory sessions.

Don’t miss this unique opportunity to learn the latest tools and approaches in addiction and genetic research, allowing students and researchers alike to return to their own communities and make meaningful contributions to science and society.

Scholarships are available!

Research reported in this publication was supported by the National Institute On Drug Abuse of the National Institutes of Health under Award Number R13DA032192.  The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The 2018 schedule is currently being developed. Please refer to the 2017 schedule for an idea of content and flow.