GTfold: enabling parallel RNA secondary structure prediction on multi-core desktops.
GTfold: enabling parallel RNA secondary structure prediction on multi-core desktops.
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gtfold：在多核桌面上启用并行RNA二级结构预测。
DOI：
10.1186/1756-0500-5-341
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发表时间：
2012-07-02
影响因子：
1.8
通讯作者：
Heitsch CE
中科院分区：
文献类型：
--
作者：
Swenson MS;Anderson J;Ash A;Gaurav P;Sükösd Z;Bader DA;Harvey SC;Heitsch CE
RNA二级结构预测是计算分子生物学中一个重要的开放性问题。从历史上看，计算技术的进步使RNA二级结构预测更快、更准确。以前的并行预测程序在运行时取得了显着的改善，但它们的实现并不便携，从利基高性能计算机或易于访问的大多数RNA研究人员。随着多核台式机的日益普及，需要一种新的并行预测程序来充分利用当今的计算技术。在这里，我们提出了第一个实现RNA二级结构预测的热力学优化现代多核计算机。我们表明，GTfold预测二级结构在更短的时间比UNAfold和RNAfold，而不牺牲准确性，在机器上有四个或更多的核心。GTfold通过减少二级结构预测的时间尺度来支持RNA结构生物学的进展。这种差异对于研究长RNA序列（如RNA病毒基因组）的研究人员特别有价值。
Accurate and efficient RNA secondary structure prediction remains an important open problem in computational molecular biology. Historically, advances in computing technology have enabled faster and more accurate RNA secondary structure predictions. Previous parallelized prediction programs achieved significant improvements in runtime, but their implementations were not portable from niche high-performance computers or easily accessible to most RNA researchers. With the increasing prevalence of multi-core desktop machines, a new parallel prediction program is needed to take full advantage of today’s computing technology. We present here the first implementation of RNA secondary structure prediction by thermodynamic optimization for modern multi-core computers. We show that GTfold predicts secondary structure in less time than UNAfold and RNAfold, without sacrificing accuracy, on machines with four or more cores. GTfold supports advances in RNA structural biology by reducing the timescales for secondary structure prediction. The difference will be particularly valuable to researchers working with lengthy RNA sequences, such as RNA viral genomes.