This workshop aims to teach participants about the application of graphs in life sciences, specifically focusing on connecting complex data. By the end of the course, learners will be able to understand graph data science and knowledge graphs for target discovery in cardiometabolic diseases, map data models to Neo4j for therapy response, build web applications for healthcare, support drug discovery using knowledge graphs, analyze co-expression networks in cancer, and more. The course utilizes a hands-on teaching method through case studies, practical examples, and panel discussions. This workshop is intended for professionals in the healthcare and life sciences industries looking to enhance their data analysis and research skills using Neo4j.
Overview
Syllabus
Neo4j Health Care & Life Sciences Workshop Day 1.
Neo4j Health Care & Life Sciences Workshop Day 2.
Neo4j Health Care & Life Sciences Workshop Day 1 - Opening.
Graph data science and knowledge graphs for target discovery for cardiometabolic diseases.
Mapping the OMOP Common Data Model to Neo4j for Pneumonia Therapy Response: SCRIPT Case Study.
Building complex Web Applications for Health Care using Neo4j.
Pegasus: a knowledge graph to support drug discovery.
HealthECCO: Bringing the world’s health knowledge to research and medical decision makers.
Analyzing Perturbed Co-Expression Networks in Cancer Using a Graph Database.
Lifelike - a graph-powered knowledge reconstruction and mining platform to accelerate research.
Graph-centric framework for translational clinical proteomics.
From Queries to Algorithms to Advanced ML: 3 Pharmaceutical Graph Use Cases.
Neo4j for Bacterial Genomes.
Modelling Multi Omics data in Neo4j to identify targets for strain development.
Unveiling the knowledge in knowledge graphs.
Evaluating Drug Safety Data Using Graph Databases.
Clinical Knowledge Graph with Spark NLP and Neo4j.
Neo4j Health Care & Life Sciences Workshop Closing Panel Discussion.
Taught by
Neo4j
