Literature DB >> 17599938

Eu.Gene Analyzer a tool for integrating gene expression data with pathway databases.

Duccio Cavalieri1, Cinzia Castagnini, Simona Toti, Karolina Maciag, Thomas Kelder, Luca Gambineri, Samuele Angioli, Piero Dolara.   

Abstract

MOTIVATION: Eu.Gene Analyzer is an easy-to-use, stand-alone application that allows rapid and powerful microarray data analysis in the context of biological pathways. Its intuitive graphical user interface makes it an easy and flexible tool, even for the first-time user. Eu.Gene supports a variety of array platforms, organisms and pathway ontologies, transparently deals with multiple nomenclature systems and seamlessly integrates data from different sources. Two different statistical methods, the Fisher Exact Test and the Gene Set Enrichment Analysis (GSEA), are implemented to identify biological pathways transcriptionally affected under experimental conditions. A suite of tools is offered to define, visualize and share custom non-redundant pathway sets. In conclusion, Eu.Gene Analyzer is a new software application that takes advantage of information from multiple pathway databases to build a comprehensive interpretation of experimental results in a simple, intuitive environment.

Mesh:

Substances:

Year:  2007        PMID: 17599938     DOI: 10.1093/bioinformatics/btm333

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  14 in total

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4.  A new permutation strategy of pathway-based approach for genome-wide association study.

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Journal:  BMC Bioinformatics       Date:  2009-12-18       Impact factor: 3.169

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

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6.  Multi-membership gene regulation in pathway based microarray analysis.

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7.  Knowledge sharing and collaboration in translational research, and the DC-THERA Directory.

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8.  ArrayIDer: automated structural re-annotation pipeline for DNA microarrays.

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Journal:  BMC Bioinformatics       Date:  2009-01-23       Impact factor: 3.169

9.  Filling gaps in PPAR-alpha signaling through comparative nutrigenomics analysis.

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10.  Presenting and exploring biological pathways with PathVisio.

Authors:  Martijn P van Iersel; Thomas Kelder; Alexander R Pico; Kristina Hanspers; Susan Coort; Bruce R Conklin; Chris Evelo
Journal:  BMC Bioinformatics       Date:  2008-09-25       Impact factor: 3.169

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