Literature DB >> 11911792

Quality control in manufacturing oligo arrays: a combinatorial design approach.

Rimli Sengupta1, Martin Tompa.   

Abstract

The advent of the DNA microarray technology has brought with it the exciting possibility of simultaneously observing the expression levels of all genes in an organism. One such microarray technology, called "oligo arrays," manufactures short single strands of DNA (called probes) onto a glass surface using photolithography. An altered or missed step in such a manufacturing protocol can adversely affect all probes using this failed step and is in general impossible to disentangle from experimental variation when using such a defective array. The idea of designing special quality control probes to detect a failed step was first formulated by Hubbell and Pevzner (1999). We consider an alternative formulation of this problem and use a combinatorial design approach to solve it. Our results improve over prior work in guaranteeing coverage of all protocol steps and in being able to tolerate a greater number of unreliable probe intensities.

Mesh:

Year:  2002        PMID: 11911792     DOI: 10.1089/10665270252833163

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  2 in total

1.  Decoding randomly ordered DNA arrays.

Authors:  Kevin L Gunderson; Semyon Kruglyak; Michael S Graige; Francisco Garcia; Bahram G Kermani; Chanfeng Zhao; Diping Che; Todd Dickinson; Eliza Wickham; Jim Bierle; Dennis Doucet; Monika Milewski; Robert Yang; Chris Siegmund; Juergen Haas; Lixin Zhou; Arnold Oliphant; Jian-Bing Fan; Steven Barnard; Mark S Chee
Journal:  Genome Res       Date:  2004-04-12       Impact factor: 9.043

2.  A microarray analysis of the rice transcriptome and its comparison to Arabidopsis.

Authors:  Ligeng Ma; Chen Chen; Xigang Liu; Yuling Jiao; Ning Su; Lin Li; Xiangfeng Wang; Mengliang Cao; Ning Sun; Xiuqing Zhang; Jingyue Bao; Jian Li; Soren Pedersen; Lars Bolund; Hongyu Zhao; Longping Yuan; Gane Ka-Shu Wong; Jun Wang; Xing Wang Deng; Jian Wang
Journal:  Genome Res       Date:  2005-09       Impact factor: 9.043

  2 in total

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