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A New Method to Predict RNA Secondary Structure Based on RNA Folding Simulation

机译:基于RNA折叠模拟的RNA二级结构预测新方法

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RNA plays an important role in various biological processes; hence, it is essential when determining the functions of RNA to research its secondary structures. So far, the accuracy of RNA secondary structure prediction remains an area in need of improvement. This paper presents a novel method for predicting RNA secondary structure based on an RNA folding simulation model. This model assumes that the process of RNA folding from the random coil state to full structure is staged and in every stage of folding, the final state of an RNA is determined by the optimal combination of helical regions, which are urgently essential to dynamics of RNA formation. This paper proposes the First Large Free Energy Difference (FLED) in order to find the helical regions most urgently needed for optimal final state formation among all the possible helical regions. Tests on the datasets with known structures from public databases demonstrate that our method can outperform other current RNA secondary structure prediction methods in terms of prediction accuracy.
机译:RNA在各种生物过程中起着重要作用;因此,在确定RNA的功能以研究其二级结构时至关重要。到目前为止,RNA二级结构预测的准确性仍然是需要改进的领域。本文提出了一种基于RNA折叠模拟模型的RNA二级结构预测新方法。该模型假设RNA从随机卷曲状态折叠到完整结构的过程是分阶段的,并且在折叠的每个阶段中,RNA的最终状态都取决于螺旋区域的最佳组合,这对于RNA的动力学至关重要编队。本文提出了“第一大自由能差”(FLED),以便在所有可能的螺旋区域中找到最理想的最终状态形成最急需的螺旋区域。对公共数据库中已知结构的数据集进行的测试表明,在预测准确性方面,我们的方法可以胜过其他当前的RNA二级结构预测方法。

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