Institut de Physique Théorique, CEA Saclay, CNRS URA 2306, 91191 Gif-sur-Yvette, France.
Nucleic Acids Res. 2011 Aug;39(14):e93. doi: 10.1093/nar/gkr240. Epub 2011 May 18.
We present TT2NE, a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus. TT2NE is guaranteed to find the minimum free energy structure regardless of pseudoknot topology. This unique proficiency is obtained at the expense of the maximum length of sequences that can be treated, but comparison with state-of-the-art algorithms shows that TT2NE significantly improves the quality of predictions. Analysis of TT2NE's incorrect predictions sheds light on the need to study how sterical constraints limit the range of pseudoknotted structures that can be formed from a given sequence. An implementation of TT2NE on a public server can be found at http://ipht.cea.fr/rna/tt2ne.php.
我们提出了 TT2NE,这是一种预测具有假结的 RNA 二级结构的新算法。该方法基于根据 RNA 结构的拓扑属对其进行分类。TT2NE 保证无论假结拓扑如何都能找到最小自由能结构。这种独特的优势是以可以处理的序列的最大长度为代价获得的,但与最先进的算法进行比较表明,TT2NE 显著提高了预测的质量。对 TT2NE 错误预测的分析揭示了需要研究如何通过立体约束限制可以从给定序列形成的假结结构的范围。在公共服务器上的 TT2NE 实现可以在 http://ipht.cea.fr/rna/tt2ne.php 找到。