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用于微阵列设计的随机探针选择算法

Randomized probe selection algorithm for microarray design.

作者信息

Gasieniec Leszek, Li Cindy Y, Sant Paul, Wong Prudence W H

机构信息

Department of Computer Science, The University of Liverpool, Ashton Building, Ashton Street, Liverpool, L69 3BX, UK.

出版信息

J Theor Biol. 2007 Oct 7;248(3):512-21. doi: 10.1016/j.jtbi.2007.05.036. Epub 2007 Jun 11.

Abstract

DNA microarray technology, originally developed to measure the level of gene expression, has become one of the most widely used tools in genomic study. The crux of microarray design lies in how to select a unique probe that distinguishes a given genomic sequence from other sequences. Due to its significance, probe selection attracts a lot of attention. Various probe selection algorithms have been developed in recent years. Good probe selection algorithms should produce a small number of candidate probes. Efficiency is also crucial because the data involved are usually huge. Most existing algorithms are usually not sufficiently selective and quite a large number of probes are returned. We propose a new direction to tackle the problem and give an efficient algorithm based on randomization to select a small set of probes and demonstrate that such a small set of probes is sufficient to distinguish each sequence from all the other sequences. Based on the algorithm, we have developed probe selection software RandPS, which runs efficiently in practice. The software is available on our website (http://www.csc.liv.ac.uk/ approximately cindy/RandPS/RandPS.htm). We test our algorithm via experiments on different genomes (Escherichia coli, Saccharamyces cerevisiae, etc.) and our algorithm is able to output unique probes for most of the genes efficiently. The other genes can be identified by a combination of at most two probes.

摘要

DNA微阵列技术最初是为测量基因表达水平而开发的,现已成为基因组研究中使用最广泛的工具之一。微阵列设计的关键在于如何选择一种独特的探针,以将给定的基因组序列与其他序列区分开来。由于其重要性,探针选择备受关注。近年来已开发出各种探针选择算法。优秀的探针选择算法应产生少量的候选探针。效率也至关重要,因为所涉及的数据通常非常庞大。大多数现有算法的选择性通常不足,会返回相当多的探针。我们提出了一种解决该问题的新方向,并给出了一种基于随机化的高效算法来选择一小部分探针,并证明这样一小部分探针足以将每个序列与所有其他序列区分开来。基于该算法,我们开发了探针选择软件RandPS,它在实际应用中运行高效。该软件可在我们的网站(http://www.csc.liv.ac.uk/ approximately cindy/RandPS/RandPS.htm)上获取。我们通过在不同基因组(大肠杆菌、酿酒酵母等)上进行实验来测试我们的算法,我们的算法能够有效地为大多数基因输出独特的探针。其他基因最多通过两个探针的组合即可识别。

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