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

被引：55

作者：

Urisman, A

Fischer, KF

Chiu, CY

Kistler, AL

Beck, S

Wang, D

DeRisi, JL ^{[1
]}

机构：

[1] Univ Calif San Francisco, Dept Biochem & Biophys, San Francisco, CA 94143 USA

[2] Univ Calif San Francisco, Biomed Sci Grad Program, San Francisco, CA 94143 USA

[3] Univ Calif San Francisco, Dept Infect Dis, San Francisco, CA 94143 USA

[4] Washington Univ, Sch Med, Dept Mol Microbiol, St Louis, MO 63110 USA

[5] Washington Univ, Sch Med, Dept Pathol, St Louis, MO 63110 USA

[6] Washington Univ, Sch Med, Dept Immunol, St Louis, MO 63110 USA

来源：

GENOME BIOLOGY | 2005年 / 6卷 / 09期

关键词：

D O I：

10.1186/gb-2005-6-9-r78

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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.

引用

页数：14

共 48 条

[1] Fine-scale phylogenetic architecture of a complex bacterial community [J].