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热力学匹配器:强化RNA折叠能的重要性。

Thermodynamic matchers: strengthening the significance of RNA folding energies.

作者信息

Höchsmann T, Höchsmann M, Giegerich R

机构信息

Faculty of Technology, University Bielefeld, Bielefeld, Germany.

出版信息

Comput Syst Bioinformatics Conf. 2006:111-21.

Abstract

Thermodynamic RNA secondary structure prediction is an important recipe for the latest generation of functional non-coding RNA finding tools. However, the predicted energy is not strong enough by itself to distinguish a single functional non-coding RNA from other RNA. Here, we analyze how well an RNA molecule folds into a particular structural class with a restricted folding algorithm called Thermodynamic Matcher (TDM). We compare this energy value to that of randomized sequences. We construct and apply TDMs for the non-coding RNA families RNA I and hammerhead ribozyme type III and our results show that using TDMs rather than universal minimum free energy folding allows for highly significant predictions.

摘要

热力学RNA二级结构预测是新一代功能性非编码RNA发现工具的重要方法。然而,预测的能量本身不足以将单个功能性非编码RNA与其他RNA区分开来。在这里,我们使用一种名为热力学匹配器(TDM)的受限折叠算法来分析RNA分子折叠成特定结构类别的程度。我们将这个能量值与随机序列的能量值进行比较。我们构建并应用了针对非编码RNA家族RNA I和III型锤头状核酶的TDM,我们的结果表明,使用TDM而不是通用的最小自由能折叠可以进行高度显著的预测。

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