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Regulatory and signaling network
assembly through Linked Open Data
Marie Lefebvre1
, Jérémie Bourdon2
, Carito Guziolowski2
, Alban Gaignard1
1
Nantes Academic Hospital, CHU de Nantes, France
2
LS2N - UMR 6004, University of Nantes, Ecole Centrale de Nantes, France
DEMO - JOBIM 2017 - LILLE
Marie Lefebvre - JOBIM 2017
CONTEXT
2
Activation
Inhibition
Gene
Complex
Signaling network
Gene Regulatory
network
Transcriptional factor
Phosphorylation
Marie Lefebvre - JOBIM 2017
CONTEXT
3
COMPUTATIONAL
PREDICTIONS
Signaling
networkGene regulatory network
Directed graphs
Precise
semantics
LOGIC AND
PROBABILISTIC
MODELS
bayesian,
boolean,
constraints based,
etc.
Marie Lefebvre - JOBIM 2017
CONTEXT
4
Signaling
networkGene regulatory network
Directed graphs
Precise
semantics
COMPUTATIONAL
PREDICTIONS
LOGIC AND
PROBABILISTIC
MODELS
bayesian,
boolean,
constraints based,
etc.
Marie Lefebvre - JOBIM 2017 5
CHALLENGE : NETWORK RECONSTRUCTION
6
3
22
1 - Multiple data sources
KEGG Pathways
✓ 514 pathways
Reactome
✓ 2132 pathways
✓ 10754 reactions
● In 2014, more than 1552 databases that are publicly accessible online (1)
● More than 31 databases useful for network construction(2)
(H. sapiens)
(1) Fernandez-Suarez X.M., and al. The 2014 Nucleic Acids Research Database Issue and an updated NAR online Molecular Biology Database
Collection. Nucleic Acids Res. 2014;42:D1–D6
(2) i.e. StringDB, intAct, GeneMania, HipathDB, WikiPathway, MetaCyc, ConsensusPathDB, etc.
Marie Lefebvre - JOBIM 2017 6
CHALLENGE : NETWORK RECONSTRUCTION
Different paths between TRAIL and FADD (apoptosis)
2 - Semantic heterogeneity
KEGG
Reactome
Marie Lefebvre - JOBIM 2017 7
CHALLENGE : NETWORK RECONSTRUCTION
Different paths between TRAIL and FADD (apoptosis)
2 - Semantic heterogeneity
KEGG
Reactome
Marie Lefebvre - JOBIM 2017
Time for 200
biological
entities input
Logic oriented
Upstream
interactions
PC Viz no result
CyPath 2 < 1min
Reactome online NA
Reactome
Cytoscape
< 1min
ChiBE < 1min
8
CHALLENGE : NETWORK RECONSTRUCTION
3 - State of the art approaches
How to discover the upstream mechanisms that trigger a list of biological entities ?
Marie Lefebvre - JOBIM 2017
OBJECTIVES
9
❖ Reconstruct a network from diverse biological entities
❖ Integrate diverse upstream regulators
❖ Large scale simulation-oriented networks
(→ predictive models)
Marie Lefebvre - JOBIM 2017 10
APPROACH
Linked Open Data
Identify &
Link Data
Querying
Reasoning
Vocabularies
Ontologies
Information
Knowledge
Marie Lefebvre - JOBIM 2017 11
OUR TOOL
BRAvo
Biological netwoRk Assembly
Marie Lefebvre - JOBIM 2017 12
IMPLEMENTATION
Database
● Store and disseminate knowledge about
biological pathways from 22 data
sources
● BioPAX level 3
● Freely available
Graph
SPARQL
endpoint
SPARQL
query
List of biological entities
Workflow
request
results
Marie Lefebvre - JOBIM 2017 13
USE CASE /1
Marie Lefebvre - JOBIM 2017 14
USE CASE /1
Marie Lefebvre - JOBIM 2017 15
USE CASE /1
Marie Lefebvre - JOBIM 2017 16
USE CASE /1
Marie Lefebvre - JOBIM 2017 17
USE CASE /2
Marie Lefebvre - JOBIM 2017 18
USE CASE /2
Marie Lefebvre - JOBIM 2017 19
USE CASE /2
Marie Lefebvre - JOBIM 2017 20
USE CASE /2
Marie Lefebvre - JOBIM 2017 21
CONCLUSION
BRAvo : Biological netwoRk Assembly
❖ Reconstruct gene regulatory network from diverse biological entities
■ From 210 entities → Time < 2min | 335 nodes & 4191 edges
❖ Integration of heterogeneous data from different data sources
❖ Designed for assembling models
❖ Available at https://github.com/symetric-group/bionets-demo
GUI Interactive reconstruction Full reconstruction BATCH
Marie Lefebvre - JOBIM 2017 22
FUTURE WORKS
● Extend type of biological entities : complex, molecule
● Add type of interaction : catalysis, phosphorylation
● Add filters (receptor)
Signaling network assembly
Integrate drug information
● Integration of KEGG drug / DrugBank
Simulation oriented controlled vocabulary
● Apply to several modeling frameworks
Package
● Provide JAVA and Python API
Thank you for your attention

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Regulatory and Signaling Network Assembly Through Linked Open Data

  • 1. Regulatory and signaling network assembly through Linked Open Data Marie Lefebvre1 , Jérémie Bourdon2 , Carito Guziolowski2 , Alban Gaignard1 1 Nantes Academic Hospital, CHU de Nantes, France 2 LS2N - UMR 6004, University of Nantes, Ecole Centrale de Nantes, France DEMO - JOBIM 2017 - LILLE
  • 2. Marie Lefebvre - JOBIM 2017 CONTEXT 2 Activation Inhibition Gene Complex Signaling network Gene Regulatory network Transcriptional factor Phosphorylation
  • 3. Marie Lefebvre - JOBIM 2017 CONTEXT 3 COMPUTATIONAL PREDICTIONS Signaling networkGene regulatory network Directed graphs Precise semantics LOGIC AND PROBABILISTIC MODELS bayesian, boolean, constraints based, etc.
  • 4. Marie Lefebvre - JOBIM 2017 CONTEXT 4 Signaling networkGene regulatory network Directed graphs Precise semantics COMPUTATIONAL PREDICTIONS LOGIC AND PROBABILISTIC MODELS bayesian, boolean, constraints based, etc.
  • 5. Marie Lefebvre - JOBIM 2017 5 CHALLENGE : NETWORK RECONSTRUCTION 6 3 22 1 - Multiple data sources KEGG Pathways ✓ 514 pathways Reactome ✓ 2132 pathways ✓ 10754 reactions ● In 2014, more than 1552 databases that are publicly accessible online (1) ● More than 31 databases useful for network construction(2) (H. sapiens) (1) Fernandez-Suarez X.M., and al. The 2014 Nucleic Acids Research Database Issue and an updated NAR online Molecular Biology Database Collection. Nucleic Acids Res. 2014;42:D1–D6 (2) i.e. StringDB, intAct, GeneMania, HipathDB, WikiPathway, MetaCyc, ConsensusPathDB, etc.
  • 6. Marie Lefebvre - JOBIM 2017 6 CHALLENGE : NETWORK RECONSTRUCTION Different paths between TRAIL and FADD (apoptosis) 2 - Semantic heterogeneity KEGG Reactome
  • 7. Marie Lefebvre - JOBIM 2017 7 CHALLENGE : NETWORK RECONSTRUCTION Different paths between TRAIL and FADD (apoptosis) 2 - Semantic heterogeneity KEGG Reactome
  • 8. Marie Lefebvre - JOBIM 2017 Time for 200 biological entities input Logic oriented Upstream interactions PC Viz no result CyPath 2 < 1min Reactome online NA Reactome Cytoscape < 1min ChiBE < 1min 8 CHALLENGE : NETWORK RECONSTRUCTION 3 - State of the art approaches How to discover the upstream mechanisms that trigger a list of biological entities ?
  • 9. Marie Lefebvre - JOBIM 2017 OBJECTIVES 9 ❖ Reconstruct a network from diverse biological entities ❖ Integrate diverse upstream regulators ❖ Large scale simulation-oriented networks (→ predictive models)
  • 10. Marie Lefebvre - JOBIM 2017 10 APPROACH Linked Open Data Identify & Link Data Querying Reasoning Vocabularies Ontologies Information Knowledge
  • 11. Marie Lefebvre - JOBIM 2017 11 OUR TOOL BRAvo Biological netwoRk Assembly
  • 12. Marie Lefebvre - JOBIM 2017 12 IMPLEMENTATION Database ● Store and disseminate knowledge about biological pathways from 22 data sources ● BioPAX level 3 ● Freely available Graph SPARQL endpoint SPARQL query List of biological entities Workflow request results
  • 13. Marie Lefebvre - JOBIM 2017 13 USE CASE /1
  • 14. Marie Lefebvre - JOBIM 2017 14 USE CASE /1
  • 15. Marie Lefebvre - JOBIM 2017 15 USE CASE /1
  • 16. Marie Lefebvre - JOBIM 2017 16 USE CASE /1
  • 17. Marie Lefebvre - JOBIM 2017 17 USE CASE /2
  • 18. Marie Lefebvre - JOBIM 2017 18 USE CASE /2
  • 19. Marie Lefebvre - JOBIM 2017 19 USE CASE /2
  • 20. Marie Lefebvre - JOBIM 2017 20 USE CASE /2
  • 21. Marie Lefebvre - JOBIM 2017 21 CONCLUSION BRAvo : Biological netwoRk Assembly ❖ Reconstruct gene regulatory network from diverse biological entities ■ From 210 entities → Time < 2min | 335 nodes & 4191 edges ❖ Integration of heterogeneous data from different data sources ❖ Designed for assembling models ❖ Available at https://github.com/symetric-group/bionets-demo GUI Interactive reconstruction Full reconstruction BATCH
  • 22. Marie Lefebvre - JOBIM 2017 22 FUTURE WORKS ● Extend type of biological entities : complex, molecule ● Add type of interaction : catalysis, phosphorylation ● Add filters (receptor) Signaling network assembly Integrate drug information ● Integration of KEGG drug / DrugBank Simulation oriented controlled vocabulary ● Apply to several modeling frameworks Package ● Provide JAVA and Python API
  • 23. Thank you for your attention