RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble
RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble
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DOI：
10.1261/rna.2500605
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发表时间：
2005-08-01
期刊：
影响因子：
4.5
通讯作者：
Lawrence, CE
中科院分区：
文献类型：
--
作者：
Ding, Y;Chan, CY;Lawrence, CE
用自由能最小化方法预测RNA二级结构已经成为二十多年来的标准。在这里，我们描述了一种新的方法，它放弃了这种范式，转而基于玻尔兹曼加权结构集成进行预测。我们引入了质心结构的概念作为一组结构的代表，并描述了识别它的过程。与使用不同类型结构RNA的最小自由能(MFE)结构相比，该集成的质心使以正预测值(PPV)衡量的预测误差减少30.0%，且灵敏度略有提高。玻尔兹曼系综可以分成少量(平均3.2个)的团簇。在这些簇的质心中，通过与已知结构比较而确定的“最佳簇质心”同时使PPV提高了46.5%，灵敏度提高了21.7%。对于58%的MFE结构位于包含最佳质心的簇之外的研究序列，最佳质心对PPV的改善为62.5%，对敏感性的改善为31.4%。这些结果表明，在目前的不完全能量模型下，含有MFE结构的能井往往不同于不可用的完整模型，后者可能包含唯一的本征结构。质心可在http://sfold.wadsworth.org.的Sold服务器上获得
Prediction of RNA secondary structure by free energy minimization has been the standard for over two decades. Here we describe a novel method that forsakes this paradigm for predictions based on Boltzmann-weighted structure ensemble. We introduce the notion of a centroid structure as a representative for a set of structures and describe a procedure for its identification. In comparison with the minimum free energy (MFE) structure using diverse types of structural RNAs, the centroid of the ensemble makes 30.0% fewer prediction errors as measured by the positive predictive value (PPV) with marginally improved sensitivity. The Boltzmann ensemble can be separated into a small number (3.2 on average) of clusters. Among the centroids of these clusters, the "best cluster centroid" as determined by comparison to the known structure simultaneously improves PPV by 46.5% and sensitivity by 21.7%. For 58% of the studied sequences for which the MFE structure is outside the cluster containing the best centroid, the improvements by the best centroid are 62.5% for PPV and 31.4% for sensitivity. These results suggest that the energy well containing the MFE structure under the current incomplete energy model is often different from the one for the unavailable complete model that presumably contains the unique native structure. Centroids are available on the Sfold server at http://sfold.wadsworth.org.