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Graphs in Life Sciences
Rik Van Bruggen
rik@neo4j.com
@rvanbruggen
Introduction to Neo4j
What We Do
7/10
20/25
7/10
Adoption
Top
Retail Firms
Top
Financial Firms
Top
Software Vendors
Customers Partners
Neo4j - The Graph Company
The Industry’s Largest Dedicated Investment in Graphs
Creator of the Market Leading
Neo4j Graph Database Platform
~420 employees
HQ in Silicon Valley, other
offices include London, Munich,
Paris & Malmö
~550 Global Enterprise
Customers
have launched a Neo4j Trial
76% of the
Industry Leaders use Neo4j
The Rise of Connections in Data
Networks of People
Know
s
Knows
Knows
Knows
Business Processes
Bought
Bought
Viewed
Returned
Bought
Knowledge Networks
Plays
Lives_in
In_sport
Likes
Fan_of
Plays_for
Data connections are increasing as rapidly as data volumes
Harnessing Connections Drives Business Value
Enhanced Decision
Making
Hyper
Personalization
Massive Data
Integration
Data Driven Discovery
& Innovation
Product Recommendations
Personalized Health Care
Media and Advertising
Fraud Prevention
Network Analysis
Law Enforcement
Drug Discovery
Intelligence and Crime Detection
Product & Process Innovation
360 view of customer
Compliance
Optimize Operations
Connected Data at the Center
AI & Machine
Learning
Price optimization
Product Recommendations
Resource allocation
Digital Transformation Megatrends
Handling Large Graph Work Loads for Enterprises
Real-time promotion
recommendations
Marriott’s Real-time
Pricing Engine
Handling Package
Routing in Real-Time
Improving Analytics, ML & AI for Enterprises
Caterpillar’s AI Supply
Chain & Maintenance
German Center for
Diabetes Research (DZD)
Financial Fraud
Detection & Recovery Top 10
Bank
Neo4j Technology
8
Neo4j is an enterprise-grade native graph database and tools:
• Store, reveal and query data relationships
• Traverse and analyze any levels of depth in real-time
• Add context and connect data to support emerging AI applications
Native Graph Technology
•
•
•
•
•
•
•
•
Labeled Property Graph - Simply Powerful
Graph Databases: Designed for Connected Data
TRADITIONAL
DATABASES
BIG DATA
TECHNOLOGY
Store and retrieve data Aggregate and filter data Connections in data
Real time storage & retrieval Real-Time Connected Insights
Long running queries
aggregation & filtering
“Our Neo4j solution is literally thousands of
times faster than the prior MySQL solution, with
queries that require 10-100 times less code”
Volker Pacher, Senior Developer
Graph databases: Designed for connected data
Connections in data
Real-Time Connected Insights
“Our Neo4j solution is literally thousands of
times faster than the prior MySQL solution, with
queries that require 10-100 times less code”
Volker Pacher, Senior Developer
Longer termbenefits:
● Ease of modelling
○ Natural fit for complex domains
○ Business savvy
○ Easy to understand and reason
● Model flexibility in an Agile world
○ Ease of maintenance
Immediate benefits
● Speed, speed, and more speed
○ enabling workloads that were thought
to be impossible before
○ real-time what was batch before
● hardware savings:
○ a few servers replacing
dozens/hundreds
● operational savings:
○ easier to run and operate
Connections in data
Real-Time Connected Insights
“Our Neo4j solution is literally thousands of
times faster than the prior MySQL solution, with
queries that require 10-100 times less code”
Volker Pacher, Senior Developer
Graph databases: Designed for connected data
Real-World
Success Stories
Highly Valuable Connected Data Use Cases
Drive Enterprise Adoption
Network &
IT Operations
Fraud
Detection
Identity & Access
Management
Knowledge
Graph
Master Data
Management
Real-Time
Recommendations
Graphs
in
Life Sciences
I will skip the part about ...
See https://www.s-cubed-global.com/news/covidgraph-nerds-response-to-the-pandemic
Graphs for
Contact Tracing
What do we mean?
Who goes into Isolation/Quarantine?
Different options
How does Contact tracing work?
Centralised or decentralised?
Centralised or Decentralised
Centralised:
• more privacy sensitive
• easier to see anomalies and
detect potentially
dangerous situations
• more valuable to see
population-wide patterns,
as well as individual health
risk benefits
• more predictive value
Decentralised:
- less privacy sensitive
- limited views possible wrt
population-wide patterns
- immediate added value to
the individual and their
health risks
Graph theory & Contact tracing
•
Networks and epidemic
models
The Model
A synthetic dataset
The Queries
Free for experimentation
Sick person visits same place as healthy person
Overlapping time in place
Most overlap = highest risk
Using inference: MEETS
match path = (p1:Person {healthstatus: "Sick"})-[m:MEETS]->(p2:Person {healthstatus: "Healthy"})
where p1.confirmedtime < m.meetingstarttime
return path
limit 100
The Analytics
Graph Data Science
Graph data science algorithms
Pagerank:
which nodes are likely to be
more important
Betweenness:
which nodes are likely to
contribute to spreading
across communities
Community Detection:
which parts of the graph
"belong" together
Graphs in Life Sciences
Recorded demo - part 1
Recorded demo - part 2
Recorded demo - part 3
Recorded demo - part 4
(synthetic)
Contact tracing
Demo
Let’s Do Something
Amazing Together

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Graphs in Life Sciences

  • 1. Graphs in Life Sciences Rik Van Bruggen rik@neo4j.com @rvanbruggen
  • 3. 7/10 20/25 7/10 Adoption Top Retail Firms Top Financial Firms Top Software Vendors Customers Partners Neo4j - The Graph Company The Industry’s Largest Dedicated Investment in Graphs Creator of the Market Leading Neo4j Graph Database Platform ~420 employees HQ in Silicon Valley, other offices include London, Munich, Paris & Malmö ~550 Global Enterprise Customers have launched a Neo4j Trial 76% of the Industry Leaders use Neo4j
  • 4. The Rise of Connections in Data Networks of People Know s Knows Knows Knows Business Processes Bought Bought Viewed Returned Bought Knowledge Networks Plays Lives_in In_sport Likes Fan_of Plays_for Data connections are increasing as rapidly as data volumes
  • 5. Harnessing Connections Drives Business Value Enhanced Decision Making Hyper Personalization Massive Data Integration Data Driven Discovery & Innovation Product Recommendations Personalized Health Care Media and Advertising Fraud Prevention Network Analysis Law Enforcement Drug Discovery Intelligence and Crime Detection Product & Process Innovation 360 view of customer Compliance Optimize Operations Connected Data at the Center AI & Machine Learning Price optimization Product Recommendations Resource allocation Digital Transformation Megatrends
  • 6. Handling Large Graph Work Loads for Enterprises Real-time promotion recommendations Marriott’s Real-time Pricing Engine Handling Package Routing in Real-Time
  • 7. Improving Analytics, ML & AI for Enterprises Caterpillar’s AI Supply Chain & Maintenance German Center for Diabetes Research (DZD) Financial Fraud Detection & Recovery Top 10 Bank
  • 9. Neo4j is an enterprise-grade native graph database and tools: • Store, reveal and query data relationships • Traverse and analyze any levels of depth in real-time • Add context and connect data to support emerging AI applications Native Graph Technology • • • • • • • •
  • 10. Labeled Property Graph - Simply Powerful
  • 11. Graph Databases: Designed for Connected Data TRADITIONAL DATABASES BIG DATA TECHNOLOGY Store and retrieve data Aggregate and filter data Connections in data Real time storage & retrieval Real-Time Connected Insights Long running queries aggregation & filtering “Our Neo4j solution is literally thousands of times faster than the prior MySQL solution, with queries that require 10-100 times less code” Volker Pacher, Senior Developer
  • 12. Graph databases: Designed for connected data Connections in data Real-Time Connected Insights “Our Neo4j solution is literally thousands of times faster than the prior MySQL solution, with queries that require 10-100 times less code” Volker Pacher, Senior Developer Longer termbenefits: ● Ease of modelling ○ Natural fit for complex domains ○ Business savvy ○ Easy to understand and reason ● Model flexibility in an Agile world ○ Ease of maintenance
  • 13. Immediate benefits ● Speed, speed, and more speed ○ enabling workloads that were thought to be impossible before ○ real-time what was batch before ● hardware savings: ○ a few servers replacing dozens/hundreds ● operational savings: ○ easier to run and operate Connections in data Real-Time Connected Insights “Our Neo4j solution is literally thousands of times faster than the prior MySQL solution, with queries that require 10-100 times less code” Volker Pacher, Senior Developer Graph databases: Designed for connected data
  • 15. Highly Valuable Connected Data Use Cases Drive Enterprise Adoption Network & IT Operations Fraud Detection Identity & Access Management Knowledge Graph Master Data Management Real-Time Recommendations
  • 17. I will skip the part about ... See https://www.s-cubed-global.com/news/covidgraph-nerds-response-to-the-pandemic
  • 19. What do we mean?
  • 20. Who goes into Isolation/Quarantine?
  • 22. How does Contact tracing work?
  • 24. Centralised or Decentralised Centralised: • more privacy sensitive • easier to see anomalies and detect potentially dangerous situations • more valuable to see population-wide patterns, as well as individual health risk benefits • more predictive value Decentralised: - less privacy sensitive - limited views possible wrt population-wide patterns - immediate added value to the individual and their health risks
  • 25. Graph theory & Contact tracing • Networks and epidemic models
  • 30. Sick person visits same place as healthy person
  • 32. Most overlap = highest risk
  • 34. match path = (p1:Person {healthstatus: "Sick"})-[m:MEETS]->(p2:Person {healthstatus: "Healthy"}) where p1.confirmedtime < m.meetingstarttime return path limit 100
  • 37. Graph data science algorithms
  • 38. Pagerank: which nodes are likely to be more important
  • 39. Betweenness: which nodes are likely to contribute to spreading across communities
  • 40. Community Detection: which parts of the graph "belong" together
  • 42. Recorded demo - part 1
  • 43. Recorded demo - part 2
  • 44. Recorded demo - part 3
  • 45. Recorded demo - part 4