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RNA-RNA Interaction Prediction and Antisense RNA Target Search

机译:RNA-RNA相互作用预测和反义RNA目标搜索

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Recent studies demonstrating the existence of special non-coding "antisense" RNAs used in post-transcriptional gene regulation have received considerable attention. These RNAs are synthesized naturally to control gene expression in C.elegans, Drosophila and other organisms; they are known to regulate plasmid copy numbers in E.coli as well. Small RNAs have also been artificially constructed to knock-out genes of interest in humans and other organisms for the purpose of finding out more about their functions. Although there are a number of algorithms for predicting the secondary structure of a single RNA molecule, no such algorithm exists for reliably predicting the joint secondary structure of two interacting RNA molecules, or measuring the stabilityof such a joint structure. In this paper, we describe the RNA-RNA interaction prediction (RIP) problem between an antisense RNA and its target mRNA and develop efficient algorithms to solve it. Our algorithms minimize the joint free-energy between the two RNA molecules under a number of energy models with growing complexity. Because the computational resources needed by our most accurate approach is prohibitive for long RNA molecules, we also describe how to speed up our techniques through a number ofheuristic approaches while experimentally maintaining the original accuracy. Equipped with this fast approach, we apply our method to discover targets for any given antisense RNA in the associated genome sequence.
机译:最近的研究表明在转录后基因调节后使用的特殊非编码“反义”RNA的存在受到相当大的关注。这些RNA自然合成以控制C.Elegans,果蝇和其他生物中的基因表达;众所周知,它们也可以调节大肠杆菌中的质粒拷贝数。小RNA也是人为地构建的,以敲出人类和其他生物的兴趣基因,以便更多地了解其功能。尽管存在许多用于预测单个RNA分子的二次结构的算法,但是不存在这种算法,用于可靠地预测两个相互作用的RNA分子的关节二次结构,或者测量这种关节结构的稳定性。在本文中,我们描述了反义RNA及其靶mRNA之间的RNA-RNA相互作用预测(RIP)问题,并开发有效的算法来解决它。我们的算法最小化了许多能量模型下的两个RNA分子之间的联合自由能量,其具有日益复杂性的能量模型。因为我们最准确的方法所需要的计算资源是望而却步长的RNA分子,我们也介绍了如何通过一些实验性的同时保持了原有的准确性ofheuristic接近加快我们的技术。配备这种快速方法,我们应用我们的方法以发现相关基因组序列中任何给定的反义RNA的目标。

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