Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree

Schliep A, Rahmann S (2006)
Bioinformatics 22(14): e424-e430.

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Autor*in
Schliep, Alexander; Rahmann, Sven
Abstract / Bemerkung
Motivation: The reliable identification of presence or absence of biological agents ("targets"), such as viruses or bacteria, is crucial for many applications from health care to biodiversity. If genomic sequences of targets are known, hybridization reactions between oligonucleotide probes and targets performed on suitable DNA microarrays will allow to infer presence or absence from the observed pattern of hybridization. Targets, for example all known strains of HIV, are often closely related and finding unique probes becomes impossible. The use of non-unique oligonucleotides with more advanced decoding techniques from statistical group testing allows to detect known targets with great success. Of great relevance, however, is the problem of identifying the presence of previously unknown targets or of targets that evolve rapidly. Results: We present the first approach to decode hybridization experiments using non-unique probes when targets are related by a phylogenetic tree. Using a Bayesian framework and a Markov chain Monte Carlo approach we are able to identify over 94% of known targets and assign up to 70% of unknown targets to their correct clade in hybridization simulations on biological and simulated data. Availability: Software implementing the method described in this paper and datasets are available from http://algorithmics.molgen.mpg.de/probetrees.
Erscheinungsjahr
2006
Band
22
Ausgabe
14
Seite(n)
e424-e430
ISSN
1367-4803
Page URI
https://pub.uni-bielefeld.de/record/1631967

Zitieren

Schliep A, Rahmann S. Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree. Bioinformatics. 2006;22(14):e424-e430.
Schliep, A., & Rahmann, S. (2006). Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree. Bioinformatics, 22(14), e424-e430. doi:10.1093/bioinformatics/btl254
Schliep, A., and Rahmann, S. (2006). Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree. Bioinformatics 22, e424-e430.
Schliep, A., & Rahmann, S., 2006. Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree. Bioinformatics, 22(14), p e424-e430.
A. Schliep and S. Rahmann, “Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree”, Bioinformatics, vol. 22, 2006, pp. e424-e430.
Schliep, A., Rahmann, S.: Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree. Bioinformatics. 22, e424-e430 (2006).
Schliep, Alexander, and Rahmann, Sven. “Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree”. Bioinformatics 22.14 (2006): e424-e430.

5 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Detecting unknown sequences with DNA microarrays: explorative probe design strategies.
Dugat-Bony E, Peyretaillade E, Parisot N, Biderre-Petit C, Jaziri F, Hill D, Rimour S, Peyret P., Environ Microbiol 14(2), 2012
PMID: 21895914
Modelling cross-hybridization on phylogenetic DNA microarrays increases the detection power of closely related species.
Engelmann JC, Rahmann S, Wolf M, Schultz J, Fritzilas E, Kneitz S, Dandekar T, Müller T., Mol Ecol Resour 9(1), 2009
PMID: 21564570
In silico microarray probe design for diagnosis of multiple pathogens.
Vijaya Satya R, Zavaljevski N, Kumar K, Bode E, Padilla S, Wasieloski L, Geyer J, Reifman J., BMC Genomics 9(), 2008
PMID: 18940003
PhylArray: phylogenetic probe design algorithm for microarray.
Militon C, Rimour S, Missaoui M, Biderre C, Barra V, Hill D, Moné A, Gagne G, Meier H, Peyretaillade E, Peyret P., Bioinformatics 23(19), 2007
PMID: 17698494

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