RNA的图论划分和伪结的分类- II
Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots-II
摘要：
对偶图已经被应用于模拟具有假结或缠结碱基对的RNA二级结构。在以前的工作中，引入了一个线性时间算法来划分对偶图成最大连通分量称为块，并确定每个块是否包含一个伪结或没有。由于假结不能包含在两个不同的块中，这种表征使我们能够有效地分离较小的RNA片段，并将其分类为假结或无假结区域，同时保持这些子结构的完整性。此外，我们已经扩展了分区算法，通过将伪结分类为递归或非递归，以继续我们的研究，在开发用于RNA设计的构建模块库的片段组装。在本文中，我们提出了一种方法，使用我们以前的结果和分类pseudoknot到经典的H，K，L和M类型，基于一种新的表示RNA二级结构的双重有向图（即，二合字母）。这种分类将有助于RNA结构的系统分析和预测，例如实现更准确的折叠算法。
英文摘要：
Dual graphs have been applied to model RNA secondary structures with pseudoknots, or intertwined base pairs. In previous works, a linear-time algorithm was introduced to partition dual graphs into maximally connected components called blocks and determine whether each block contains a pseudoknot or not. As pseudoknots can not be contained into two different blocks, this characterization allow us to efficiently isolate smaller RNA fragments and classify them as pseudoknotted or pseudoknot-free regions, while keeping these sub-structures intact. Moreover we have extended the partitioning algorithm by classifying a pseudoknot as either recursive or non-recursive in order to continue with our research in the development of a library of building blocks for RNA design by fragment assembly. In this paper we present a methodology that uses our previous results and classify pseudoknots into the classical H,K,L, and M types, based upon a novel representation of RNA secondary structures as dual directed graphs (i.e., digraphs). This classification would help the systematic analysis of RNA structure and prediction as for example the implementation of more accurate folding algorithms.
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