E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns
E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns
复制标题
DOI：
10.1186/gb-2005-6-9-r78
复制
发表时间：
2005-01-01
期刊：
影响因子：
12.3
通讯作者：
DeRisi, JL
中科院分区：
文献类型：
--
作者：
Urisman, A;Fischer, KF;DeRisi, JL
DNA微阵列可用于鉴定环境和临床样品中存在的微生物种类。然而，缺乏基于观察到的微阵列杂交模式进行可靠物种鉴定的自动化工具。我们提出了一种基于微阵列的物种识别算法E-Forecast。E-Forecast将观察到的杂交模式与代表不同物种的理论能量分布进行比较。我们在一组临床样本中演示了该算法在病毒检测中的应用，并讨论了它与其他元基因组应用的相关性。
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.