Pain Adrien, Ott Alban, Amine Hamza, Rochat Tatiana, Bouloc Philippe, Gautheret Daniel
a Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS ; Université Paris-Sud ; Orsay Cedex , France.
RNA Biol. 2015;12(5):509-13. doi: 10.1080/15476286.2015.1020269.
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.
大多数细菌调控RNA通过与靶RNA碱基配对发挥功能。靶标的计算预测是一个活跃的研究领域，为生物学家提供了各种网站和软件。然而，非专业人员很难评估这些程序的可靠性。在此，我们基于可靠的大肠杆菌sRNA/靶标对，为细菌sRNA靶标预测提供了一个简单的基准。我们使用这个基准来评估最新的RNA靶标预测器以及早期的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。与以前的软件相比，利用靶标保守性和可及性信息的最新算法提高了准确性。然而，即使使用最好的预测器，低分的真正生物学靶标和高分的非靶标的数量仍然令人困惑。
