Cargando…

ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis

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 seemi...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Guanming, Dawson, Eric, Duong, Adrian, Haw, Robin, Stein, Lincoln
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4184317/
https://www.ncbi.nlm.nih.gov/pubmed/25309732
http://dx.doi.org/10.12688/f1000research.4431.2
_version_ 1782337825955381248
author Wu, Guanming
Dawson, Eric
Duong, Adrian
Haw, Robin
Stein, Lincoln
author_facet Wu, Guanming
Dawson, Eric
Duong, Adrian
Haw, Robin
Stein, Lincoln
author_sort Wu, Guanming
collection PubMed
description 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 combined with human curated pathways derived 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.
format Online
Article
Text
id pubmed-4184317
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher F1000Research
record_format MEDLINE/PubMed
spelling pubmed-41843172014-10-09 ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis Wu, Guanming Dawson, Eric Duong, Adrian Haw, Robin Stein, Lincoln F1000Res Software Tool 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 combined with human curated pathways derived 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. F1000Research 2014-09-12 /pmc/articles/PMC4184317/ /pubmed/25309732 http://dx.doi.org/10.12688/f1000research.4431.2 Text en Copyright: © 2014 Wu G et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/publicdomain/zero/1.0/ Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
spellingShingle Software Tool
Wu, Guanming
Dawson, Eric
Duong, Adrian
Haw, Robin
Stein, Lincoln
ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis
title ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis
title_full ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis
title_fullStr ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis
title_full_unstemmed ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis
title_short ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis
title_sort reactomefiviz: a cytoscape app for pathway and network-based data analysis
topic Software Tool
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4184317/
https://www.ncbi.nlm.nih.gov/pubmed/25309732
http://dx.doi.org/10.12688/f1000research.4431.2
work_keys_str_mv AT wuguanming reactomefivizacytoscapeappforpathwayandnetworkbaseddataanalysis
AT dawsoneric reactomefivizacytoscapeappforpathwayandnetworkbaseddataanalysis
AT duongadrian reactomefivizacytoscapeappforpathwayandnetworkbaseddataanalysis
AT hawrobin reactomefivizacytoscapeappforpathwayandnetworkbaseddataanalysis
AT steinlincoln reactomefivizacytoscapeappforpathwayandnetworkbaseddataanalysis