Supporting RNAstructure: Software for RNA Analysis

描述：快速测序方法已经确定了生命所有领域的功能RNA序列。确定这些RNA序列的作用及其作用机制对生物学和人类健康至关重要。RNA二级结构预测是帮助理解RNA功能的常用工具之一，我们通过开发RNA结构解决了对RNA二级结构预测的需求。RNAStructure是一个用于RNA二级结构预测、显示和分析的用户友好的软件包。它包括用于单个序列的结构预测的方法，包括伪结点、双分子相互作用的结构预测和多个同源序列的保守结构的预测。为RNA和DNA序列提供了热力学参数，这将结构预测扩展到DNA。这些程序有图形用户界面(Windows、Mac OS X或Linux)、命令行界面，也可以作为Web服务器使用。这些算法也可以作为一组文档良好的C++类在其他程序中使用。在GNU公共许可证下，该包是完全开源的。这项提议是为了继续开发和维护该软件。对于下一阶段的支持，我们将提出高影响力的目标，以保持RNA结构的尖端和用户友好。我们将开发一个新的界面，便于比较序列分析来确定保守的RNA结构，继续支持和扩展现有的程序和界面，并开发一种新的假结序列结构预测方法。

DESCRIPTION: Rapid sequencing methods have identified functional RNA sequences across all domains of life. Determining the roles of these RNA sequences and their mechanisms of action is central to biology and human health. RNA secondary structure prediction is one of the tools that is commonly used to aid in understanding RNA function, and we have addressed the need for RNA secondary structure prediction by developing RNAstructure. RNAstructure is a user-friendly software package for RNA secondary structure prediction, display, and analysis. It includes methods for structure prediction of a single sequence, including pseudoknots, structure prediction for bimolecular interactions, and prediction of the conserved structure for multiple homologous sequences. Thermodynamic parameters are provided for both RNA and DNA sequences, which extends the structure predictions to DNA. The programs are available with a graphical user interface (for Windows, Mac OS X, or Linux), command line interfaces, and also as web servers. The algorithms are also available for use in other programs as a set of well-documented C++ classes. The package is fully open source, under the GNU Public License. This proposal is for continued development and maintenance of the software. For the next period of support, we are proposing high-impact aims that will keep RNAstructure cutting-edge and user-friendly. We will develop a new interface for facilitating comparative sequence analysis to determine a conserved RNA structure, continue to support and extend the existing programs and interfaces, and develop a new method for structure prediction for pseudoknotted sequences.