CANCELLED – April 16-17, 2020

Facilitators: Laura Ibañez and Victoria Fernandez (Cruchaga lab; WashU Psychiatry)

A two-day workshop on Machine Learning as applied to OMICs data, accompanied by lectures each day. The workshop and lectures are made possible by a Chan Zuckerberg Initiative (CZI) award to post docs in a CZI-funded team, the Office of Neuroscience Research (ONR), the Neurogenomics and Informatics (NGI) Group, the McDonnell Genome Institute (MGI), the Department of Genetics and the WashU Postdoctoral Society.

Registration is required for the 2-day workshop, but not for the plenary lectures. Additional details for the workshop/hands on training will be sent directly to registrants.

Notes from the workshop organizers – Please read!

  • Registration is required, though completion of the registration form does not guarantee a spot.  Priority will be given to graduate students and post docs with representation across departments.
  • The registration form is open until February 28.  Registrants will learn of acceptance at the beginning of March.  At that time, a fee of $30 will be required to complete registration.
  • We strongly recommend a basic knowledge of Unix, R, and Python to attend this workshop.
  • Each participant is required to bring a personal laptop.  Additional information for required software to be installed will be provided to registered participants.

Preliminary schedule

Thursday, April 16 (8a – 5p)

  • Introduction to Big Data and Machine Learning in Biological Data
  • Supervised methods: Which method, what for, which R/Python package?
  • Hands on Part I: Feature Selection – Random Forest and Regression (Lasso/Elastic Nets)
  • Hands on Part II: Deep Neural Networks (Tensor Flow)
  • Invited lecture: Effective use of machine learning in Genetic data (Dr. James Zou, Stanford University)

Friday, April 17 (8a – 5p)

  • Unsupervised methods: tools and usages for biological datasets
  • Hands on Part I: Dimensional reduction – principal components and networks
  • Hands on Part II: clustering
  • Invited lecture: Multi-omics data integration (Dr. Shuangee Steven Ma, Yale University)