Höchsmann Matthias, Voss Björn, Giegerich Robert
International Graduate School in Bioinformatics and Genome Research, University of Bielefeld, Bielefeld, Germany.
IEEE/ACM Trans Comput Biol Bioinform. 2004 Jan-Mar;1(1):53-62. doi: 10.1109/TCBB.2004.11.
In functional, noncoding RNA, structure is often essential to function. While the full 3D structure is very difficult to determine, the 2D structure of an RNA molecule gives good clues to its 3D structure, and for molecules of moderate length, it can be predicted with good reliability. Structure comparison is, in analogy to sequence comparison, the essential technique to infer related function. We provide a method for computing multiple alignments of RNA secondary structures under the tree alignment model, which is suitable to cluster RNA molecules purely on the structural level, i.e., sequence similarity is not required. We give a systematic generalization of the profile alignment method from strings to trees and forests. We introduce a tree profile representation of RNA secondary structure alignments which allows reasonable scoring in structure comparison. Besides the technical aspects, an RNA profile is a useful data structure to represent multiple structures of RNA sequences. Moreover, we propose a visualization of RNA consensus structures that is enriched by the full sequence information.
在功能性非编码RNA中,结构往往对功能至关重要。虽然完整的三维结构很难确定,但RNA分子的二维结构能为其三维结构提供很好的线索,对于中等长度的分子,其二维结构可以较为可靠地预测。与序列比较类似,结构比较是推断相关功能的关键技术。我们提供了一种在树形比对模型下计算RNA二级结构多重比对的方法,该方法适用于仅在结构层面上对RNA分子进行聚类,即不需要序列相似性。我们对从字符串到树和森林的轮廓比对方法进行了系统的推广。我们引入了一种RNA二级结构比对的树形轮廓表示法,它能在结构比较中进行合理的打分。除了技术方面,RNA轮廓是一种表示RNA序列多种结构的有用数据结构。此外,我们提出了一种能通过完整序列信息得到丰富的RNA共有结构可视化方法。