Introducing the community to the most cutting-edge methods of data acquisition and analysis through direct training
Questions about past or future workshops? Contact the Office of Neuroscience Research.
Open Source Workshops
Facilitators: Meaghan Creed (WashU Psychiatry), Lex Kravitz (WashU Psychiatry), Martha Bagnall (WashU Dept of Neuroscience)
Supported by the Washington University Pain Center, the McDonnell Center for Systems Neuroscience, and the Office of Neuroscience Research.
VIRTUAL SimBA: July 2020
Facilitators: Sam Golden and Simon Nilsson (University of Washington)
An open source toolkit for computer classification of complex social behaviors in experimental animals
Arduino: Feb 2020
Facilitator: Lex Kravitz (WashU Psychiatry)
Affordable open-source electronics platform with easy-to-use hardware and software
DeepLabCut™: July 2019
Facilitator: Martha Bagnall (WashU Dept of Neuroscience)
For 3D markerless pose estimation based on transfer learning with deep neural networks
VIRTUAL B-SOiD: April 2020; follow-up session May 2020
Facilitators: Alexander Hsu and Eric Yttri (Carnegie Mellon U)
An open source unsupervised algorithm for discovery of spontaneous behaviors
Bonsai: Oct 2019
Facilitator: Meaghan Creed (WashU Anesthesiology)
Visual language for software systems that require rich and rapid interaction with the external world
VIRTUAL Application of Machine Learning Tools to OMICs in Neuroscience
Facilitators: Laura Ibañez and Victoria Fernandez (WashU Psychiatry)
Supported by the Chan Zuckerberg Initiative, the Office of Neuroscience Research, the Neurogenomics and Informatics Center, the McDonnell Genome Institute, the Department of Genetics and the WashU Postdoc Society (WUPS).
A virtual one day event! Basic introductory sessions to Machine Learning, two plenary lectures, oral presentations and round table.
February 18, 2021
- Introduction to Machine Learning by Dr. Noah Simon (University of Washington)
- Types of ML: Supervised by Dr. Justin Miller (Brigham Young University)
- Effective use of ML in Genetic Data by Dr. James Zou (Stanford University)
- Multi–omic Data Integration, Implications for the Medical Field by Dr. Shuangge Steven Ma (Yale University)
- Types of ML: Unsupervised by Dr. Justin Miller (Brigham Young University)
