公开(公告)号：US20050240563A1

公开(公告)日：2005-10-27

申请号：US11154542

申请日：2005-06-17

申请人： Eytan Domany ,  Gad Getz ,  Erel Levine

发明人： Eytan Domany ,  Gad Getz ,  Erel Levine

IPC分类号： G01N20060101 ,  G06F19/20 ,  G06F19/24 ,  G06F7/00

CPC分类号： G06F19/24 ,  G06F19/20 ,  G06K9/6219 ,  Y10S707/99937

摘要： A novel coupled two-way clustering approach to gene microarray data analysis, for identifying subsets of the genes and samples, such that when one of these items is used to cluster the other, stable and significant partitions emerge. The method of the present invention preferably uses iterative clustering in order to execute this search in an efficient way. This approach is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method of the present invention was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on these subsets, partitions and correlations were found that were masked and hidden when the full data set was used in the analysis.

公开(公告)号：US07599933B2

公开(公告)日：2009-10-06

申请号：US11154542

申请日：2005-06-17

申请人： Eytan Domany ,  Gad Getz ,  Erel Levine

发明人： Eytan Domany ,  Gad Getz ,  Erel Levine

IPC分类号： G06F17/30 ,  G06F19/00

CPC分类号： G06F19/24 ,  G06F19/20 ,  G06K9/6219 ,  Y10S707/99937

摘要： A novel coupled two-way clustering approach to gene microarray data analysis, for identifying subsets of the genes and samples, such that when one of these items is used to cluster the other, stable and significant partitions emerge. The method of the present invention preferably uses iterative clustering in order to execute this search in an efficient way. This approach is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method of the present invention was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on these subsets, partitions and correlations were found that were masked and hidden when the full data set was used in the analysis.

摘要翻译： 一种新颖的双向聚类方法，用于基因芯片数据分析，用于识别基因和样本的子集，使得当这些项目中的一个被用于聚集另一个项目时，出现稳定和显着的分区。 本发明的方法优选地使用迭代聚类，以便以有效的方式执行该搜索。 这种方法特别适用于基因微阵列数据，其中各种生物机制对基因表达水平的贡献在大量实验数据中纠缠。 将本发明的方法应用于结肠癌和白血病的两个基因微阵列数据集。 通过识别数据的相关子集并集中在这些子集上，当分析中使用完整的数据集时，发现分区和相关性被掩蔽和隐藏。

公开(公告)号：US06965831B2

公开(公告)日：2005-11-15

申请号：US10220702

申请日：2001-03-09

申请人： Eytan Domany ,  Gad Getz ,  Erel Levine

发明人： Eytan Domany ,  Gad Getz ,  Erel Levine

IPC分类号： G01N20060101 ,  G06F19/20 ,  G06F19/24 ,  G06F19/00

CPC分类号： G06F19/24 ,  G06F19/20 ,  G06K9/6219 ,  Y10S707/99937

摘要： A novel coupled two-way clustering approach to gene microarray data analysis, for identifying subsets of the genes and samples, such that when one of these items is used to cluster the other, stable and significant partitions emerge. The method of the present invention preferably uses iterative clustering in order to execute this search in an efficient way. This approach is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method of the present invention was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on these subsets, partitions and correlations were found that were masked and hidden when the full data set was used in the analysis.

摘要翻译： 一种新颖的双向聚类方法，用于基因芯片数据分析，用于识别基因和样本的子集，使得当这些项目中的一个被用于聚集另一个项目时，出现稳定和显着的分区。 本发明的方法优选地使用迭代聚类，以便以有效的方式执行该搜索。 这种方法特别适用于基因微阵列数据，其中各种生物机制对基因表达水平的贡献在大量实验数据中纠缠。 将本发明的方法应用于结肠癌和白血病的两个基因微阵列数据集。 通过识别数据的相关子集并集中在这些子集上，当分析中使用完整的数据集时，发现分区和相关性被掩蔽和隐藏。