Reactome: a database of reactions, pathways and biological processes

Abstract

Reactome (http://www.reactome.org) is a collaboration among groups at the Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University School of Medicine and The European Bioinformatics Institute, to develop an open source curated bioinformatics database of human pathways and reactions. Recently, we developed a new web site with improved tools for pathway browsing and data analysis. The Pathway Browser is an Systems Biology Graphical Notation (SBGN)-based visualization system that supports zooming, scrolling and event highlighting. It exploits PSIQUIC web services to overlay our curated pathways with molecular interaction data from the Reactome Functional Interaction Network and external interaction databases such as IntAct, BioGRID, ChEMBL, iRefIndex, MINT and STRING. Our Pathway and Expression Analysis tools enable ID mapping, pathway assignment and overrepresentation analysis of user-supplied data sets. To support pathway annotation and analysis in other species, we continue to make orthology-based inferences of pathways in non-human species, applying Ensembl Compara to identify orthologs of curated human proteins in each of 20 other species. The resulting inferred pathway sets can be browsed and analyzed with our Species Comparison tool. Collaborations are also underway to create manually curated data sets on the Reactome framework for chicken, Drosophila and rice.

Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease

“…To generate a generic network for studying the effect of the lipids on the cellular metabolism, we expanded the coverage of the HMR database. We first merged metabolism of lipids and lipoproteins in Reactome, a manually curated and peer-reviewed pathway database 61 , and the literature-based GEMs including Recon 1 (ref. 12), EHMN 13,14 and HepatoNet 1, a manually reconstructed GEM for hepatocytes 1 .…”

Cross-cancer profiling of molecular alterations within the human autophagy interaction network

“…1) was generated using the Reactome Functional Interaction database Plugin 2 for Cytoscape 2.8.0 85,86 to illustrate high-confidence known and predicted human PPIs, between 162 members of the gene set that had manually-curated PPIs available. Using the Reactome Cluster FI network algorithm, 9,85 we further grouped PPIs identified within the gene set into modules with higher than expected intra-cluster connectivity versus inter-cluster connectivity. To highlight important cellular pathways reported to affect autophagy status, we annotated modules with significantly enriched (FDR < 0.01) GO biological process terms of member AA proteins.…”

Analysis of the genomic response of human prostate cancer cells to histone deacetylase inhibitors

“…These collections included, among others, the Human Protein Reference Database (HPRD), GO, Kyoto Encyclopedia of Genes and Genomes (KEGG), the Molecular Signature Database (MSigDB), the Pathway Commons and NCBI Entrez Gene databases. 14,[21][22][23][24][25][26][27][28][29][30] FGS whose expression altered most significantly upon HDACinhibition in DU-145 and PC3 cells across all conditions after correction for multiple testing (adjusted P value < 0.05, top five FGS or more in case of ties), were retrieved and are displayed in Figure 1. This approach enabled the identification of biological themes that are differentially expressed upon HDAC-inhibition across all conditions irrespective of the gene expression direction change (Fig.…”