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E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns.

ABSTRACT: DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a set of clinical samples and discuss its relevance to other metagenomic applications.

SUBMITTER: Urisman A

PROVIDER: S-EPMC1242213 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

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E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns.

Urisman Anatoly A Fischer Kael F KF Chiu Charles Y CY Kistler Amy L AL Beck Shoshannah S Wang David D DeRisi Joseph L JL

Genome biology 20050830 9

DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a ...[more]

PMID: 16168085

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