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Deterministic Approach for Biclustering of Co-Regulated Genes from Gene Expression Data

机译:基因表达数据共调节基因双面的决定性方法

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This paper presents an expression pattern based biclustering technique for grouping both positively and negatively regulated genes together as co-regulated genes from microarray expression data. Most interesting variants of this problem are NP-complete requiring either large computational effort or the use of lossy heuristics to short circuit the calculation. Our approach deterministically finds all biclusters using a non-greedy approach in polynomial time. Various real datasets have been used for experiments and results are excellent.
机译:本文介绍了一种基于表达模式的双层技术,用于将阳性和负调节基因分组为来自微阵列表达数据的共调节基因。这个问题的最有趣的变体是NP-Comploy,需要大的计算工作或使用有损启发式来短路计算。我们的方法在多项式时间中使用非贪婪的方法来确定所有Biclusters。各种真实数据集已用于实验,结果优异。

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