Reactome: a database of reactions, pathways and biological processes

@article{Croft2010ReactomeAD,
  title={Reactome: a database of reactions, pathways and biological processes},
  author={David Croft and Gavin O'Kelly and Guanming Wu and Robin Haw and Marc E. Gillespie and Lisa Matthews and Michael Caudy and Phani V. Garapati and Gopal R. Gopinath and Bijay Jassal and Steven Jupe and Irina Kalatskaya and Shahana S Mahajan and Bruce May and Nelson Ndegwa and Esther Schmidt and Veronica Shamovsky and Christina K. Yung and Ewan Birney and Henning Hermjakob and Peter D’Eustachio and Lincoln Stein},
  journal={Nucleic Acids Research},
  year={2010},
  volume={39},
  pages={D691 - D697}
}
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… 

Reactome pathway analysis to enrich biological discovery in proteomics data sets

This Tutorial provides an intuitive web‐based user interface to pathway knowledge and a suite of data analysis tools that provide a platform for data mining, modeling and analysis of large‐scale proteomics data sets.

Using the Reactome Database

This unit describes how to use the Reactome database to learn the steps of a biological pathway; navigate and browse through thereactome database; identify the pathways in which a molecule of interest is involved; and use the Pathway and Expression analysis tools to search the database for and visualize possible connections within user‐supplied experimental data set and Reactome pathways.

The Reactome Pathway Knowledgebase

To support the continued brisk growth in the size and complexity of Reactome, this work has implemented a graph database, improved performance of data analysis tools, and designed new data structures and strategies to boost diagram viewer performance.

The Reactome pathway Knowledgebase

The Reactome Knowledgebase (www.reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular

Integrating in silico resources to map a signaling network.

Generation of composite interaction networks enables investigators to extract significantly more information about a given biological system than utilization of a single database or sole reliance on primary literature.

IPAVS: Integrated Pathway Resources, Analysis and Visualization System

Integrated Pathway Resources, Analysis and Visualization System (iPAVS) is an integrated biological pathway database designed to support pathway discovery in the fields of proteomics,

PathRings: a web-based tool for exploration of ortholog and expression data in biological pathways

PathRings has been designed to accommodate interactive visual analysis of experimental data in the context of pathways defined by Reactome, and a dynamic multi-view bubbles interface is designed to support biologists' analytical tasks by letting users construct incremental views that further reflect biologists’ analytical process.

The ConsensusPathDB interaction database: 2013 update

ConsensusPathDB has grown mainly due to the integration of 12 further databases; it now contains 215 541 unique interactions and 4601 pathways from overall 30 databases, and has re-implemented the graph visualization feature of Consensus pathDB using the Cytoscape.js library.

KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases

A web server, KOBAS 2.0, is reported, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations, which allows for both ID mapping and cross-species sequence similarity mapping.

Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome

Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell, and adapted the Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways.
...

References

SHOWING 1-10 OF 42 REFERENCES

Reactome knowledgebase of human biological pathways and processes

Improved orthology prediction methods allowing pathway inference for 22 species and through collaborations to create manually curated Reactome pathway datasets for species including Arabidopsis, Oryza sativa, Drosophila and Gallus gallus.

PID: the Pathway Interaction Database

The Pathway Interaction Database (PID), a freely available collection of curated and peer-reviewed pathways composed of human molecular signaling and regulatory events and key cellular processes, serves as a research tool for the cancer research community and others interested in cellular pathways.

The systematic annotation of the three main GPCR families in Reactome

The first catalogue of all human G protein-coupled receptors (GPCRs) known to bind endogenous or natural ligands is built, creating reactions in which 563 GPCRs bind ligands and also interact with specific G-proteins to initiate signalling cascades.

A human functional protein interaction network and its application to cancer data analysis

A highly reliable functional interaction network upon expert-curated pathways is built and applied to the analysis of two genome-wide GBM and several other cancer data sets, suggesting common mechanisms in the cancer biology.

STRING 8—a global view on proteins and their functional interactions in 630 organisms

The most important new developments in STRING 8 over previous releases include a URL-based programming interface, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures.

MINT, the molecular interaction database: 2012 update

The growth of the database, the major changes in curation policy and a new algorithm to assign a confidence to each interaction are reported here.

GSEA-P: a desktop application for Gene Set Enrichment Analysis

A new version of the Java based software (GSEA-P 2.0) is reported that represents a major improvement on the previous release through the addition of a leading edge analysis component, seamless integration with the Molecular Signature Database (MSigDB) and an embedded browser that allows users to search for gene sets and map them to a variety of microarray platform formats.

Database resources of the National Center for Biotechnology Information: update

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in

The IntAct molecular interaction database in 2010

In response to the growing data volume and user requests, IntAct now provides a two-tiered view of the interaction data, which allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies.

Text mining and manual curation of chemical-gene-disease networks for the Comparative Toxicogenomics Database (CTD)

This text-mining project is unique in its integration of existing tools into a single workflow with direct application to CTD, which allowed us to measure the potential of these integrated tools to improve prioritization of journal articles for manual curation.