Literature DB >> 17069516

Functional interpretation of microarray experiments.

Joaquín Dopazo1.   

Abstract

Over the past few years, due to the popularisation of high-throughput methodologies such as DNA microarrays, the possibility of obtaining experimental data has increased significantly. Nevertheless, the interpretation of the results, which involves translating these data into useful biological knowledge, still remains a challenge. The methods and strategies used for this interpretation are in continuous evolution and new proposals are constantly arising. Initially, a two-step approach was used in which genes of interest were initially selected, based on thresholds that consider only experimental values, and then in a second, independent step the enrichment of these genes in biologically relevant terms, was analysed. For different reasons, these methods are relatively poor in terms of performance and a new generation of procedures, which draw inspiration from systems biology criteria, are currently under development. Such procedures, aim to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes.

Mesh:

Year:  2006        PMID: 17069516     DOI: 10.1089/omi.2006.10.398

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  34 in total

1.  Class-specific correlations of gene expressions: identification and their effects on clustering analyses.

Authors:  Jigang Zhang; Jian Li; Hongwen Deng
Journal:  Am J Hum Genet       Date:  2008-08       Impact factor: 11.025

2.  GREAT improves functional interpretation of cis-regulatory regions.

Authors:  Cory Y McLean; Dave Bristor; Michael Hiller; Shoa L Clarke; Bruce T Schaar; Craig B Lowe; Aaron M Wenger; Gill Bejerano
Journal:  Nat Biotechnol       Date:  2010-05-02       Impact factor: 54.908

3.  Transcriptome analysis identifies TNF superfamily receptors as potential therapeutic targets in alcoholic hepatitis.

Authors:  Silvia Affò; Marlene Dominguez; Juan José Lozano; Pau Sancho-Bru; Daniel Rodrigo-Torres; Oriol Morales-Ibanez; Montserrat Moreno; Cristina Millán; Aurora Loaeza-del-Castillo; José Altamirano; Juan Carlos García-Pagán; Vicente Arroyo; Pere Ginès; Juan Caballería; Robert F Schwabe; Ramon Bataller
Journal:  Gut       Date:  2012-05-25       Impact factor: 23.059

4.  Multidimensional gene set analysis of genomic data.

Authors:  David Montaner; Joaquín Dopazo
Journal:  PLoS One       Date:  2010-04-27       Impact factor: 3.240

5.  Functional profiling and gene expression analysis of chromosomal copy number alterations.

Authors:  Lucía Conde; David Montaner; Jordi Burguet-Castell; Joaquín Tárraga; Fátima Al-Shahrour; Joaquín Dopazo
Journal:  Bioinformation       Date:  2007-04-10

6.  WhichGenes: a web-based tool for gathering, building, storing and exporting gene sets with application in gene set enrichment analysis.

Authors:  Daniel Glez-Peña; Gonzalo Gómez-López; David G Pisano; Florentino Fdez-Riverola
Journal:  Nucleic Acids Res       Date:  2009-04-30       Impact factor: 16.971

7.  GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information.

Authors:  Ruben Nogales-Cadenas; Pedro Carmona-Saez; Miguel Vazquez; Cesar Vicente; Xiaoyuan Yang; Francisco Tirado; Jose María Carazo; Alberto Pascual-Montano
Journal:  Nucleic Acids Res       Date:  2009-05-22       Impact factor: 16.971

8.  Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies.

Authors:  Ignacio Medina; David Montaner; Nuria Bonifaci; Miguel Angel Pujana; José Carbonell; Joaquin Tarraga; Fatima Al-Shahrour; Joaquin Dopazo
Journal:  Nucleic Acids Res       Date:  2009-06-05       Impact factor: 16.971

9.  Gene set internal coherence in the context of functional profiling.

Authors:  David Montaner; Pablo Minguez; Fátima Al-Shahrour; Joaquín Dopazo
Journal:  BMC Genomics       Date:  2009-04-27       Impact factor: 3.969

10.  From disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose ontology for the test of gene-ontology associations.

Authors:  Pan Du; Gang Feng; Jared Flatow; Jie Song; Michelle Holko; Warren A Kibbe; Simon M Lin
Journal:  Bioinformatics       Date:  2009-06-15       Impact factor: 6.937

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