Literature DB >> 14962679

ExQuest, a novel method for displaying quantitative gene expression from ESTs.

Aaron C Brown1, Kristin Kai, Marjorie E May, Donald C Brown, Derry C Roopenian.   

Abstract

There is a pressing need for interactive bioinformatics tools that empower investigators with the means to extract information and organize it in a simplified but meaningful format. A wealth of mammalian gene expression data is readily accessible, much of which is based on expressed sequence tags (ESTs). Many mammalian ESTs are derived from tissue-specific cDNA libraries in which the number of ESTs representing a specific gene approximates the transcriptional expression level in the source tissue. Our program ExQuest (Expressional Quantification of ESTs) organizes the public EST database (dbEST) into hierarchical tissue classes and reports tissue or developmental gene expression patterns for both mRNA and genomic sequences. ExQuest also displays tissue expression patterns of genes in the context of assembled chromosomes. These interactive "transcriptome" maps provide a novel tool for investigating the genomic basis of gene expression as well as prioritizing candidate genes within genetically mapped mutant and quantitative trait loci.

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Mesh:

Year:  2004        PMID: 14962679     DOI: 10.1016/j.ygeno.2003.09.012

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  9 in total

Review 1.  Data-mining technologies for diabetes: a systematic review.

Authors:  Miroslav Marinov; Abu Saleh Mohammad Mosa; Illhoi Yoo; Suzanne Austin Boren
Journal:  J Diabetes Sci Technol       Date:  2011-11-01

2.  Quantitative gene expression profiles in real time from expressed sequence tag databases.

Authors:  Vincent A Funari; Konstantin Voevodski; Dimitry Leyfer; Laura Yerkes; Donald Cramer; Dean R Tolan
Journal:  Gene Expr       Date:  2010

3.  Quantitative gene expression profiling implicates genes for susceptibility and resistance to alveolar bone loss.

Authors:  G T Hart; D J Shaffer; S Akilesh; A C Brown; L Moran; D C Roopenian; P J Baker
Journal:  Infect Immun       Date:  2004-08       Impact factor: 3.441

4.  The use of EST expression matrixes for the quality control of gene expression data.

Authors:  Andrew T Milnthorpe; Mikhail Soloviev
Journal:  PLoS One       Date:  2012-03-08       Impact factor: 3.240

5.  Quantitative comparison of EST libraries requires compensation for systematic biases in cDNA generation.

Authors:  Donglin Liu; Joel H Graber
Journal:  BMC Bioinformatics       Date:  2006-02-17       Impact factor: 3.169

6.  In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues.

Authors:  Sheng-Ying Pao; Win-Li Lin; Ming-Jing Hwang
Journal:  BMC Genomics       Date:  2006-04-21       Impact factor: 3.969

7.  Generation of a large scale repertoire of Expressed Sequence Tags (ESTs) from normalised rainbow trout cDNA libraries.

Authors:  Marina Govoroun; Florence Le Gac; Yann Guiguen
Journal:  BMC Genomics       Date:  2006-08-03       Impact factor: 3.969

8.  Searching QTL by gene expression: analysis of diabesity.

Authors:  Aaron C Brown; William I Olver; Charles J Donnelly; Marjorie E May; Jürgen K Naggert; Daniel J Shaffer; Derry C Roopenian
Journal:  BMC Genet       Date:  2005-03-10       Impact factor: 2.797

9.  Beyond tissueInfo: functional prediction using tissue expression profile similarity searches.

Authors:  Daniel Aguilar; Lucy Skrabanek; Steven S Gross; Baldo Oliva; Fabien Campagne
Journal:  Nucleic Acids Res       Date:  2008-05-15       Impact factor: 16.971

  9 in total

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