Sixing Huang - MGI
Presentation: https://www.slideshare.net/neo4j/neo4j-for-bacterial-genomes
With some simple steps, we can import the public relational data into Neo4j and quickly visualize the data, calculate statistics and do machine learning. In this presentation, I am going to show you how to use Neo4j to analyze bacterial genomes, enzymes and antibiotic resistance. I will use Neo4j Browser and Bloom to visualize the data and Graph Data Science plugin to do machine learning.
Our third Neo4j Health Care & Life Sciences Workshop has been set up to showcase practical solutions to common problems as well as helping to incubate collaboration, innovation and good practice. Graph databases are powerful tools that are inherently capable of managing vast quantities of data points and the web of relationships between them. As people start turning to tools like Neo4j for answers there are inevitably more questions: data modeling, performance, resilience, interoperability. These are the kinds of questions we want to help you answer.
Learn more: https://development.neo4j.dev/use-cases/life-sciences/