How to SGBA: Ask Me Anything

This event is an extension of our "How to SGBA" workshop series and is organized by our SGBA Working Group. It is intended to provide a low barrier, casual opportunity for anyone to ask an SGBA expert questions about how to integrate SGBA into their research. We welcome all interested members of the community, including trainees, early career or senior faculty, and senior scientists to attend and ask about SGBA research.

The SGBA Expert for this event will be Dr. Elizabeth Rideout - think of it as an informal office hour where you can pop in whenever you'd like and chat about SGBA! While we can't guarantee we'll have all the answers, we will try out best to point you in the right direction. You can ask any question that you have about SGBA. We have listed a few examples below to help you get started. All questions are welcome!

Sample examples include:

• "What statistical tests do I use to see if there is a sex difference?"
• "If I don't know what causes the difference, can I publish my findings?"
• "What is the best way to visualize differences?"
• "Funding is limited and I can't afford to do all my experiments in both sexes. What should I do?"

The event will take place on Zoom:
https://ubc.zoom.us/j/69164397720?pwd=ckxBZ2pHMHdIMlREV0F1eFQvbGNtUT09

Meeting ID: 691 6439 7720
Passcode: 625202

SGBA EXPERT

Dr. Elizabeth Rideout Dr. Elizabeth Rideout is an Assistant Professor in the Department of Cellular and Physiological Sciences, and is affiliated with the Women's Health Research Institute and Women's Health Research Cluster. Dr. Rideout holds a CIHR Sex and Gender Science Chair in Genetics, and is a Michael Smith Foundation for Health Research Scholar. Her research uses Drosophila as a model to understand how sex differences in metabolism contribute to male-female differences in body fat, body size, and aging. The overarching goal of Dr. Rideout's research is to identify specific genes and pathways that contribute to sex differences in metabolism, and to understand how the abnormal function or regulation of these genes and pathways influences the risk of developing metabolic diseases such as obesity, diabetes, and cardiovascular disease. Twitter: @EJRideout