www.reactome.org

A curated database of biological pathways

Why are pathways important?

• Deep response• Pathways are how cells work - going beyond the “parts list”

into mechanisms at the cellular level is a fundamental advance in knowledge.

• Shallow response• Lots of ‘Omics’ datasets require data integration.

Reactome is …

• Manually curated and peer-reviewed database of pathways and

processes in human biology

• Open source and open access

• Basic Unit of Reactome = “Reaction”

• Extensively cross-referenced

• Infer orthologous events in non-human species (Data Expansion)

• M/O Reactomes: Arabidopsis, Gallus, Drosophila, (Oryzae)

• Provides tools for browsing, searching, analyzing and visualizing

pathway data – Pathway Analysis, Expression Overlay, Species

Comparison, Biomart…

• Data Portability – BioPAX, SBML, PSI-MITAB, etc.

Visualization

www.reactome.org

4

Reactome Home Page

Data Visualization and Analysis

Human EGFR Pathway

ID Mapping, Over-representation and expression analysis

Increasing Coverage:Reactome Functional Interaction Network

Data Sources

Pathway databases

Protein-protein interactions

Shared GO terms

Gene co-expression data

Transcription factors/targets

Literature mining

10,956 proteins (58% in pathways)209,988 interactions (47% in pathways)

46% coverage of UniProt

Figure: 15% of the combined network

• Networks provide better coverage and when combined with pathway information can offer clues to mechanism.

• Add non-Reactome data sets to create a “corona” of interaction data around each pathway.

Human EGFR Pathway

Molecular Interaction Overlay – PSIQUIC WS

PSICQUIC RegistryAPIDBIND

BioGridChEMBL

DIPInnateDB

IntActiRefIndexMatrixDB

MINTMPIDB

ReactomeReactome-FIs

STRING

Data Exchange Formats

• Promote data integration, analysis and visualization.

• PSI MITAB – representing interaction data* (*infer interactions from the complexes

and reactions).

• SBML – representing models of biochemical pathways, reactions and networks.

• BioPAX – used for representing pathway and network data.

Integrative Data Analysis using Reactome Functional Interaction Network Cytoscape Plug-in

Guanming Wu, Irina Kalatskaya, Christina Yung

Expt/Clinical DataReactome F.I. Network

Extract mutated, over-expressed, down-regulated, amplified,

deleted genes

Disease/Cancer

Subnetwork

Disease/Cancer

“Modules”

Apply clustering algorithms

Pathway Annotation

DatasetsT2DGBM

Ovarian CancerBreast Cancer

Prostate CancerTCGAICGC

Create a Biological Hypothesis!Predict Disease Gene Function

Classify Patients & Samples

Programmatic Access

• Application programming interfaces (API) are important to connect and automate data exchange between local programs and databases.

• BioMart API• MySQL/Perl API• MySQL/Java API • SOAP/WSDL • Flat files• Database dumps• Local site install

Uber-portal Integration (Data Warehouses) and other exports

Other Data Exports

• Gene Ontology, Protein Ontology

• HapMap and UCSC Genome Browsers

• GSEA

• WikiPathways, Wormbase, PDB

Summary

• Pathway databases are an integral part of the scientific enterprise.

• Reactome has deployed a user-friendly web site that promotes

integrated research on pathways and networks.

• Data visualization

• Data analysis

• Data expansion

• Data integration

• Data standards/exports

• Develop and distribute open software and standard operating

procedures for the management of pathway information.

Credits

OICR/CSHL NYU EBI

Lincoln Stein Peter D'Eustachio Ewan Birney

Michael Caudy Shahana Mahajan Henning Hermjakob

Marc Gillespie Lisa Matthews David Croft

Robin Haw Veronica Shamovsky Phani Garapati

Irina Kalatskaya Bijay Jassal

Bruce May Steven Jupe

Leontius Pradhana

Nelson Ndegwa

Guanming Wu Gavin O’Kelly

Christina Yung Esther Schmidt

Supported by grants from the US National Institutes of Health (P41 HG003751) and EU grant LSHG-CT-2005-518254 "ENFIN”