An assessment of bacterial small RNA target prediction programs.
An assessment of bacterial small RNA target prediction programs.
复制标题
DOI：
10.1080/15476286.2015.1020269
复制
发表时间：
2015
期刊：
影响因子：
4.1
通讯作者：
Gautheret D
中科院分区：
文献类型：
--
作者：
Pain A;Ott A;Amine H;Rochat T;Bouloc P;Gautheret D
大多数细菌调节RNA通过与靶RNA的碱基配对发挥其功能。目标的计算预测是一个忙碌的研究领域，为生物学家提供了各种网站和软件。然而，非专家很难评估这些程序的可靠性。在这里，我们提供了一个简单的基准细菌sRNA目标预测的基础上可信的E。coli sRNA/target pairs。我们使用这个基准来评估最新的RNA靶预测因子以及早期的RNA-RNA杂交预测程序。此外，我们考虑mRNA边界的定义如何影响整体预测。最近的算法，利用保护的目标和可访问性信息提供了改进的准确性比以前的软件。然而，即使有最好的预测因子，得分低的真正生物靶点和得分高的非靶点的数量仍然令人困惑。
Most bacterial regulatory RNAs exert their function through base-pairing with target RNAs. Computational prediction of targets is a busy research field that offers biologists a variety of web sites and software. However, it is difficult for a non-expert to evaluate how reliable those programs are. Here, we provide a simple benchmark for bacterial sRNA target prediction based on trusted E. coli sRNA/target pairs. We use this benchmark to assess the most recent RNA target predictors as well as earlier programs for RNA-RNA hybrid prediction. Moreover, we consider how the definition of mRNA boundaries can impact overall predictions. Recent algorithms that exploit both conservation of targets and accessibility information offer improved accuracy over previous software. However, even with the best predictors, the number of true biological targets with low scores and non-targets with high scores remains puzzling.