重组酵母基因表达数据
Shuffling Yeast Gene Expression Data
摘要：
提出了一种将基因表达模式按功能分组的新方法。该方法基于使用非局部相似性得分的排序算法，该算法考虑了数据集中的所有其他模式。因此，该方法相对于噪声是非常鲁棒的。使用酵母的表达数据，我们提取有关官能团的信息。在没有参数的先验知识的情况下，可以鉴定酵母中的细胞周期调控基因。此外，识别第二独立单元时钟。该算法的能力，以提取信息的信号流在监管网络的表达模式的基础上证明。
英文摘要：
A new method to sort gene expression patterns into functional groups is presented. The method is based on a sorting algorithm using a non-local similarity score, which takes all other patterns in the dataset into account. The method is therefore very robust with respect to noise. Using the expression data for yeast, we extract information about functional groups. Without prior knowledge of parameters the cell cycle regulated genes in yeast can be identified. Furthermore a second, independent cell clock is identified. The capability of the algorithm to extract information about signal flow in the regulatory network underlying the expression patterns is demonstrated.
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