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首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >Nonparametric Clustering for Studying RNA Conformations
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Nonparametric Clustering for Studying RNA Conformations

机译：非参数聚类研究RNA构象

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摘要

The local conformation of RNA molecules is an important factor in determining their catalytic and binding properties. The analysis of such conformations is particularly difficult due to the large number of degrees of freedom, such as the measured torsion angles per residue and the interatomic distances among interacting residues. In this work, we use a nearest-neighbor search method based on the statistical mechanical Potts model to find clusters in the RNA conformational space. The proposed technique is mostly automatic and may be applied to problems, where there is no prior knowledge on the structure of the data space in contrast to many other clustering techniques. Results are reported for both single residue conformations, where the parameter set of the data space includes four to seven torsional angles, and base pair geometries, where the data space is reduced to two dimensions. Moreover, new results are reported for base stacking geometries. For the first two cases, i.e., single residue conformations and base pair geometries, we get a very good match between the results of the proposed clustering method and the known classifications with only few exceptions. For the case of base stacking geometries, we validate our classification with respect to geometrical constraints and describe the content, and the geometry of the new clusters.
机译：RNA分子的局部构象是决定其催化和结合特性的重要因素。由于存在许多自由度，例如每个残基的测得的扭转角和相互作用残基之间的原子间距离，因此对此类构象进行分析特别困难。在这项工作中，我们使用基于统计机械Potts模型的最近邻搜索方法来查找RNA构象空间中的簇。与许多其他聚类技术相比，所提出的技术大部分都是自动的，可以应用于问题，在这些问题上，我们对数据空间的结构没有先验知识。报告了两个残基构象的结果，其中数据空间的参数集包括四个到七个扭转角，以及碱基对的几何形状，其中数据空间减小到了二维。此外，据报道，基本堆叠的几何结构也有了新的结果。对于前两种情况，即单个残基构象和碱基对的几何形状，我们将提出的聚类方法的结果与已知的分类结果很好地匹配，只有少数例外。对于基本堆叠的几何形状，我们根据几何约束条件验证分类，并描述内容和新群集的几何形状。

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