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首页> 外文期刊>IEEE/ACM transactions on computational biology and bioinformatics >Efficient Algorithms for the Computational Design of Optimal Tiling Arrays
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Efficient Algorithms for the Computational Design of Optimal Tiling Arrays

机译：最优平铺阵列计算设计的高效算法

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摘要

The representation of a genome by oligonucleotide probes is a prerequisite for the analysis of many of its basic properties, such as transcription factor binding sites, chromosomal breakpoints, gene expression of known genes and detection of novel genes, in particular those coding for small RNAs. An ideal representation would consist of a high density set of oligonucleotides with similar melting temperatures that do not cross-hybridize with other regions of the genome and are equidistantly spaced. The implementation of such design is typically called a tiling array or genome array. We formulate the minimal cost tiling path problem for the selection of oligonucleotides from a set of candidates. Computing the selection of probes requires multi-criterion optimization, which we cast into a shortest path problem. Standard algorithms running in linear time allow us to compute globally optimal tiling paths from millions of candidate oligonucleotides on a standard desktop computer for most problem variants. The solutions to this multi-criterion optimization are spatially adaptive to the problem instance. Our formulation incorporates experimental constraints with respect to specific regions of interest and trade offs between hybridization parameters, probe quality and tiling density easily.
机译：用寡核苷酸探针代表基因组是分析其许多基本特性的先决条件，例如转录因子结合位点，染色体断点，已知基因的基因表达以及检测新基因，尤其是编码小RNA的基因。理想的代表是由高密度的一组寡核苷酸组成，这些寡核苷酸具有相似的解链温度，不会与基因组的其他区域交叉杂交，并且等距分布。这种设计的实现通常称为平铺阵列或基因组阵列。我们制定了从一组候选物中选择寡核苷酸的最小成本平铺路径问题。计算探针的选择需要多准则优化，我们将其引入了最短路径问题。在线性时间内运行的标准算法使我们能够针对大多数问题变体，从标准台式计算机上的数百万个候选寡核苷酸计算全局最优分片路径。此多准则优化的解决方案在空间上适应问题实例。我们的配方结合了针对特定目标区域的实验约束，并在杂交参数，探针质量和切片密度之间轻松权衡。

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