Gruber Andreas R, Findeiß Sven, Washietl Stefan, Hofacker Ivo L, Stadler Peter F
Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany.
Pac Symp Biocomput. 2010:69-79.
RNAz is a widely used software package for de novo detection of structured noncoding RNAs in comparative genomics data. Four years of experience have not only demonstrated the applicability of the approach, but also helped us to identify limitations of the current implementation. RNAz 2.0 provides significant improvements in two respects: (1) The accuracy is increased by the systematic use of dinucleotide models. (2) Technical limitations of the previous version, such as the inability to handle alignments with more than six sequences, are overcome by increased training data and the usage of an entropy measure to represent sequence similarities. RNAz 2.0 shows a significantly lower false discovery rate on a dinucleotide background model than the previous version. Separate models for structural alignments provide an additional way to increase the predictive power. RNAz is open source software and can be obtained free of charge at: http://www.tbi.univie.ac.at/~wash/RNAz/
RNAz是一个广泛用于在比较基因组学数据中从头检测结构化非编码RNA的软件包。四年的经验不仅证明了该方法的适用性，也帮助我们识别了当前实现方式的局限性。RNAz 2.0在两个方面有显著改进：（1）通过系统使用二核苷酸模型提高了准确性。（2）通过增加训练数据以及使用熵度量来表示序列相似性，克服了先前版本的技术局限性，如无法处理多于六个序列的比对。在二核苷酸背景模型上，RNAz 2.0的错误发现率明显低于先前版本。用于结构比对的单独模型提供了另一种提高预测能力的方法。RNAz是开源软件，可从以下网址免费获取：http://www.tbi.univie.ac.at/~wash/RNAz/
