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Statistical Methods for the Discovery of Co-operative Transcription Factors: the Co-bind Code Revised

机译:发现合作转录因子的统计方法:修订的共绑定代码

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Discovering co-operative Transcription Factors (TF's) within the genome is a computationally challenging problem, tackled through Monte Carlo-like analysis by the Co-Bind code, developed at the Department of Genetics of the St. Louis Washington University. Due to its statistical nature, Co-Bind is characterized by very long execution times, order of days on current high-end workstations, and could benefit from parallelization and a wise optimization, performed at both the algorithmic and coding levels. This work presents the results achieved by parallelizing Co-Bind and optimising the parallel code and shows that, on a 16-processor architecture, a speedup greater than two orders of magnitude is achieved with respect to the serial version released by the code's authors.
机译:在基因组中发现合作转录因子(TF)是一个计算上有挑战性的问题,通过CO-BIND代码通过蒙特卡罗的分析来解决,在圣路易斯华盛顿大学遗传学系开发。由于其统计性质,共结合的特征在于执行时间非常长,当前高端工作站上的天数,并且可以从算法和编码水平进行并行化和明智的优化中受益。这项工作提出了通过并行化CO-BIND并优化并行代码来实现的结果,并显示在16处理器架构上,对于代码作者发布的串行版本,实现了大于两个数量级的加速。

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