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  Fast large scale oligonucleotide selection using the longest common factor approach

Rahmann, S. (2003). Fast large scale oligonucleotide selection using the longest common factor approach. Journal of Bioinformatics and Computational Biology, 1(2), 343-361.

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Genre: Zeitschriftenartikel
Alternativer Titel : J Bioinf Comp Biol

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 Urheber:
Rahmann, Sven1, Autor           
Affiliations:
1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              

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Schlagwörter: Microarray; oligo selection; probe design; suffix array; matching statistics; longest common substring; longest common factor
 Zusammenfassung: We present a fast method that selects oligonucleotide probes (such as DNA 25-mers) for microarray experiments on a truly large scale. For example, reliable oligos for human genes can be found within four days, a speedup of one to two orders of magnitude compared to previous approaches. This speed is attained by using the longest common substring as a specificity measure for candidate oligos. We present a space- and time-efficient algorithm, based on a suffix array with additional information, to compute matching statistics (lengths of longest matches) between all candidate oligos and all remaining sequences. With the matching statistics available, we show how to incorporate constraints such as oligo length, melting temperature, and self-complementarity into the selection process at a postprocessing stage. As a result, we can now design custom oligos for any sequenced genome, just as the technology for on-site chip synthesis is becoming increasingly mature.

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Sprache(n): eng - English
 Datum: 2003-02
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: eDoc: 176095
 Art des Abschluß: -

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Titel: Journal of Bioinformatics and Computational Biology
  Alternativer Titel : J Bioinf Comp Biol
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 1 (2) Artikelnummer: - Start- / Endseite: 343 - 361 Identifikator: ISSN: 0219-7200