Data Science Training Program
Alex Pico, PhD
This course is a complement to “Introduction to Network Biology and Cytoscape”. Following a brief review of the key concepts of network analysis, you'll embark on a deep dive into data visualization and advanced Cytoscape features.
We will work through three prepared use cases demonstrating various omics data types and strategies, but you’re encouraged to bring your own data as well.
By the end of this course you will be able to:
- Know when and how to use Cytoscape in your research
- Handle multiple data types in Cytoscape
- Transform and merge data with networks from multiple sources
- Master customized data visualization
- Navigate the greater Cytoscape ecosystem.
Prerequisites: You should already be familiar with Cytoscape and the fundamentals of network analysis. Bring a laptop with the latest version of Cytoscape installed.
Intermediate: This is an intermediate workshop in the Network Analysis and Visualization series. You should already be familiar with Cytoscape prior to attending this workshop. See introductory course:
Visit the workshop site for more details and materials
DatesMarch 9, 2023
AudienceGladstone and UCSF
The Gladstone Data Science Training Program was started in 2018 to provide trainees with learning opportunities and hands-on workshops to improve their skills in bioinformatics and computational analysis. This program offers a series of workshops throughout the year to enable trainees to gain new skills and get support with their questions and data.
Diversity, Equity, and Inclusion
At Gladstone, we are committed to providing events and professional development activities that resonate with our community’s diverse members. Our goal is to develop creative programming that encompasses a wide variety of ideas and perspectives to inspire, educate, and engage with everyone within our walls.
We want to effect positive change through our events and activities by providing a platform for discussions on important topics related to increasing diversity and inclusiveness in the sciences.