Literature DB >> 10462419

Expression profiling: DNA arrays in many guises.

S Granjeaud1, F Bertucci, B R Jordan.   

Abstract

DNA arrays have become the preferred method for large-scale expression measurement. Such data are needed in view of the large amounts of sequence data available: expression levels in a number of different tissues or situations provide a first step toward functional characterisation of new entities revealed by DNA sequencing. Although the basic principle of measurement is in all cases based on hybridisation of a mixed probe derived from tissue RNA to large sets of DNA fragments representing many genes, a number of different forms of implementation of this principle are at hand. They are briefly described and compared, emphasizing the important issue of sensitivity and sample requirements and the accessibility of the methods to academic scientists. When these factors are taken into account, it appears that, contrary to a largely prevalent impression, the "best" approach is not necessarily always provided by the widely advertised glass microarrays or oligonucleotide chips. Copyright 1999 John Wiley & Sons, Inc.

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Year:  1999        PMID: 10462419     DOI: 10.1002/(SICI)1521-1878(199909)21:9<781::AID-BIES10>3.0.CO;2-2

Source DB:  PubMed          Journal:  Bioessays        ISSN: 0265-9247            Impact factor:   4.345


  17 in total

1.  Normalization strategies for cDNA microarrays.

Authors:  J Schuchhardt; D Beule; A Malik; E Wolski; H Eickhoff; H Lehrach; H Herzel
Journal:  Nucleic Acids Res       Date:  2000-05-15       Impact factor: 16.971

Review 2.  Microarrays under the microscope.

Authors:  S E Wildsmith; F J Elcock
Journal:  Mol Pathol       Date:  2001-02

3.  Quantitative transcript imaging in normal and heat-shocked Drosophila embryos by using high-density oligonucleotide arrays.

Authors:  R Leemans; B Egger; T Loop; L Kammermeier; H He; B Hartmann; U Certa; F Hirth; H Reichert
Journal:  Proc Natl Acad Sci U S A       Date:  2000-10-24       Impact factor: 11.205

4.  Determining the identifiability of DNA database entries.

Authors:  B Malin; L Sweeney
Journal:  Proc AMIA Symp       Date:  2000

Review 5.  Molecular detection of antimicrobial resistance.

Authors:  A C Fluit; M R Visser; F J Schmitz
Journal:  Clin Microbiol Rev       Date:  2001-10       Impact factor: 26.132

6.  Subsystem identification through dimensionality reduction of large-scale gene expression data.

Authors:  Philip M Kim; Bruce Tidor
Journal:  Genome Res       Date:  2003-07       Impact factor: 9.043

7.  Identification of genes preferentially expressed during wood formation in Eucalyptus.

Authors:  Etienne Paux; M'Barek Tamasloukht; Nathalie Ladouce; Pierre Sivadon; Jacqueline Grima-Pettenati
Journal:  Plant Mol Biol       Date:  2004-05       Impact factor: 4.076

8.  Gene expression profiling of bone cells on smooth and rough titanium surfaces.

Authors:  J Harle; V Salih; I Olsen; P Brett; F Jones; M Tonetti
Journal:  J Mater Sci Mater Med       Date:  2004-11       Impact factor: 3.896

9.  How to improve quality assurance in fluorometry: fluorescence-inherent sources of error and suited fluorescence standards.

Authors:  U Resch-Genger; K Hoffmann; W Nietfeld; A Engel; J Neukammer; R Nitschke; B Ebert; R Macdonald
Journal:  J Fluoresc       Date:  2005-05       Impact factor: 2.217

Review 10.  Genomic platforms for cancer research: potential diagnostic and prognostic applications in clinical oncology.

Authors:  Pedro Jares; Elías Campo
Journal:  Clin Transl Oncol       Date:  2006-03       Impact factor: 3.405

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