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 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 Registry APID BIND BioGrid ChEMBL DIP InnateDB IntAct iRefIndex MatrixDB MINT MPIDB Reactome Reactome-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/Canc er Subnetwork Disease/Ca ncer “Modules” Apply clustering algorithms Pathway Annotation Datasets T2D GBM Ovarian Cancer Breast Cancer Prostate Cancer TCGA ICGC 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/CSHLNYUEBI Lincoln SteinPeter D'EustachioEwan Birney Michael CaudyShahana MahajanHenning Hermjakob Marc GillespieLisa MatthewsDavid Croft Robin HawVeronica ShamovskyPhani Garapati Irina KalatskayaBijay Jassal Bruce MaySteven Jupe Leontius PradhanaNelson Ndegwa Guanming WuGavin O’Kelly Christina YungEsther Schmidt Supported by grants from the US National Institutes of Health (P41 HG003751) and EU grant LSHG-CT "ENFIN”