Literature DB >> 12141992

Bioinformatics methods for the analysis of expression arrays: data clustering and information extraction.

Javier Tamames1, Dominic Clark, Javier Herrero, Joaquín Dopazo, Christian Blaschke, José M Fernández, Juan C Oliveros, Alfonso Valencia.   

Abstract

Expression arrays facilitate the monitoring of changes in the expression patterns of large collections of genes. The analysis of expression array data has become a computationally-intensive task that requires the development of bioinformatics technology for a number of key stages in the process, such as image analysis, database storage, gene clustering and information extraction. Here, we review the current trends in each of these areas, with particular emphasis on the development of the related technology being carried out within our groups.

Mesh:

Year:  2002        PMID: 12141992     DOI: 10.1016/s0168-1656(02)00137-2

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  7 in total

1.  Global transcriptional response of Bacillus subtilis to treatment with subinhibitory concentrations of antibiotics that inhibit protein synthesis.

Authors:  Janine T Lin; Mariah Bindel Connelly; Chris Amolo; Suzie Otani; Debbie S Yaver
Journal:  Antimicrob Agents Chemother       Date:  2005-05       Impact factor: 5.191

2.  GOAL: automated Gene Ontology analysis of expression profiles.

Authors:  Stefano Volinia; Rita Evangelisti; Francesca Francioso; Diego Arcelli; Massimo Carella; Paolo Gasparini
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

3.  Clustering of gene expression data: performance and similarity analysis.

Authors:  Longde Yin; Chun-Hsi Huang; Jun Ni
Journal:  BMC Bioinformatics       Date:  2006-12-12       Impact factor: 3.169

4.  SILAC-iPAC: a quantitative method for distinguishing genuine from non-specific components of protein complexes by parallel affinity capture.

Authors:  Johanna S Rees; Kathryn S Lilley; Antony P Jackson
Journal:  J Proteomics       Date:  2014-12-20       Impact factor: 4.044

5.  DNA microarray data and contextual analysis of correlation graphs.

Authors:  Jacques Rougemont; Pascal Hingamp
Journal:  BMC Bioinformatics       Date:  2003-04-29       Impact factor: 3.169

6.  Statistical modelling of transcript profiles of differentially regulated genes.

Authors:  Daniel C Eastwood; Andrew Mead; Martin J Sergeant; Kerry S Burton
Journal:  BMC Mol Biol       Date:  2008-07-23       Impact factor: 2.946

7.  The chicken B-cell line DT40 proteome, beadome and interactomes.

Authors:  Johanna S Rees; Kathryn S Lilley; Antony P Jackson
Journal:  Data Brief       Date:  2015-01-13
  7 in total

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