Gaining insight into molecular content and associated relationships in an age of big data is challenging. The web holds a vast corpus of scientific data in a multiplicity of machine-readable formats. The data is scattered all over the internet in numerous formats and with multiple associations derived from a variety of sources. Resources such as Google BigQuery are ideal for performing big data analysis and complex SQL queries in this environment. However, interrogating and visualizing large datasets and their relationships is difficult.  This talk will present an investigative analysis on a new visual analytics platform, GraphXR.  In conjunction with Google’s BigQuery, GraphXR facilitates scientific discovery in applications ranging from clinical studies to counterterrorism.  Use-cases showing the analysis of relationships of molecular content across multiple domains will be presented.

Visualizing relationships of molecular content in a big data environment

ACS Spring 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.