Sign:高性能计算的大规模基因网络估计环境。

Y. Tamada, Teppei Shimamura, R. Yamaguchi, S. Imoto, Masao Nagasaki, S. Miyano
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引用次数: 17

摘要

我们的研究小组目前正在开发从基因表达数据估计大规模基因网络的软件。该软件名为SiGN,是专门为日本旗舰超级计算机“K计算机”设计的,该计算机计划在2012年实现每秒10千万亿次浮点运算,以及包括人类基因组中心(HGC)超级计算机系统在内的其他高性能计算环境。SiGN是一个基因网络估计软件的集合,有三个不同的子程序:SiGN- bn, SiGN- ssm和SiGN- l1。在这三个程序中,有五种不同的模型可用:静态和动态非参数贝叶斯网络,状态空间模型,图形高斯模型和向量自回归模型。所有这些模型都需要大量的计算资源来估计大规模的基因网络,因此被设计为能够利用每秒10千万亿次的速度。该软件将免费提供给“K计算机”和HGC超级计算机系统用户。估计的网络可以通过Cell Illustrator Online和ship(系统生物学整合管道)进行查看和分析。该软件项目的网址是http://sign.hgc.jp/。
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Sign: large-scale gene network estimation environment for high performance computing.
Our research group is currently developing software for estimating large-scale gene networks from gene expression data. The software, called SiGN, is specifically designed for the Japanese flagship supercomputer "K computer" which is planned to achieve 10 petaflops in 2012, and other high performance computing environments including Human Genome Center (HGC) supercomputer system. SiGN is a collection of gene network estimation software with three different sub-programs: SiGN-BN, SiGN-SSM and SiGN-L1. In these three programs, five different models are available: static and dynamic nonparametric Bayesian networks, state space models, graphical Gaussian models, and vector autoregressive models. All these models require a huge amount of computational resources for estimating large-scale gene networks and therefore are designed to be able to exploit the speed of 10 petaflops. The software will be available freely for "K computer" and HGC supercomputer system users. The estimated networks can be viewed and analyzed by Cell Illustrator Online and SBiP (Systems Biology integrative Pipeline). The software project web site is available at http://sign.hgc.jp/ .
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Docking-calculation-based method for predicting protein-RNA interactions. Sign: large-scale gene network estimation environment for high performance computing. Linear regression models predicting strength of transcriptional activity of promoters. Database for crude drugs and Kampo medicine. Mechanism of cell cycle disruption by multiple p53 pulses.
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