Reactome: new publications available
Members of the Reactome team at EMBL-EBI have recently published the following papers about this open resource for molecular pathway data.
Jupe, S., Jassal, B., Williams, M. and Wu, G. (2014) A controlled vocabulary for pathway entities and events. Database 2014:bau060. DOI:10.1093/database/bau060
Entities involved in pathways and the events they participate in require descriptive and unambiguous names that are often not available in the literature or elsewhere. Reactome is a manually curated, open-source resource of human pathways. It is accessible via a website, available as downloads in standard reusable formats and via Representational State Transfer (REST)-ful and Simple Object Access Protocol (SOAP) application programming interfaces (APIs). We have devised a controlled vocabulary (CV) that creates concise, unambiguous and unique names for reactions (pathway events) and all the molecular entities they involve. The CV could be reapplied in any situation where names are used for pathway entities and events. Adoption of this CV would significantly improve naming consistency and readability, with consequent benefits for searching and data mining within and between databases.
Wu, G., Dawson, E., Duong, A., Haw, R. and Stein, L. (2014) ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis. F1000Research 3, 146. DOI:10.12688/f1000research.4431.1
High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network and human curated pathways from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.
A full list of Reactome team publications can be found on the Reactome website.