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Thomas Kelder, PhD
Using graphs to decipher
complexity of health and disease
Graph Database Meetup, Amsterdam, 5 November 2014
This presentation remains property of EdgeLeap B.V. and is licensed for reuse under a Creative Commons Attribution 4.0 International License (see http://creativecommons.org/licenses/by/4.0/).
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GRAPHS @ EDGELEAP
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Diameter of the World-wide WebAlbert, Jeong and Barabási, Nature 1999
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PERSONAL HEALTH IS COMPLEX
Organs
Person
Cells
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DATA!
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IMAGINE POPULATION HEALTH!
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ITERATIVE DISCOVERY
INTERVENE
UNDERSTAND
VISUALIZE
MINE
INTEGRATE
MEASURE
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GRAPH OF DISEASES
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GRAPH OF ADIPOSE HEALTH
Kelder, et al., Genes & Nutrition (2014), in press
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NEO4J IN BIOLOGY
CyNeo4J by Georg Summerhttp://cyneo4j.wordpress.com/
Storage & Calculation Analysis & Visualization
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PHARMA CASE:
TARGET PRIORITIZATION
• Target prioritization for drug development
• Narrow down from >1000 potential targets to ~10 best candidates
• Make smart choice, account for complex underlying biology!
• Biological context
• Centrality
• Affected processes
• Druggability
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REACTOME PATHWAY DATABASE
• Known biological pathways
• Relational database
• Complex data model (249 tables)
• Model pathways, events, proteins as graph
• 1,597 signaling pathways
• 7,597 unique proteins
• 6,467 reactions
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EXAMPLE:
SIGNALING PATHWAYS
Signal input
Effect
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PATHWAY IN NEO4J
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PROXIMITY BY SHORTEST PATH
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PROXIMITY FOR ALL PROTEINS
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REAL LIFE EXAMPLE
16
Random
Classical bioinformatics
Prioritization based ongraph models
Benchmark prioritization techniques by recovery of known relevant genes.
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PEAK INTO THE FUTURE
JAN FEB MAR APR MAY JUN
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THANKS!
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edgeleap
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Marijana RadonjicEdgeLeap
Georg SummerUM & TNO
