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    • 43. 发明授权
    • Characterization of phenotypes by gene expression patterns and classification of samples based thereon
    • 通过基因表达模式表征表型并基于样品的分类
    • US07860660B2
    • 2010-12-28
    • US12574195
    • 2009-10-06
    • Andrea CalifanoGustavo A. StolovitzkyYuhai Tu
    • Andrea CalifanoGustavo A. StolovitzkyYuhai Tu
    • G06F19/00G06F17/18G01N31/00
    • G06F19/24G06F19/20
    • Generally, the present invention applies a transformation to convert a probability distribution of gene expression signals in control samples to a uniform distribution. The uniform distribution allows better comparisons between expression levels for genes. The transformation is derived from gene expression signals of control data, and is applied to gene expression signals of phenotype data. The phenotype data can be represented in a matrix format. A number of gene expression patterns may be determined (in the form of submatrices) that will characterize the phenotype. The uniform distribution helps in this regard, as it allows better comparisons of patterns. The gene expression patterns can then be used to classify samples as belonging to the phenotype set. Preferably, a discriminant function is used to compare a sample with the gene expression patterns that characterize the phenotype. The discriminant function can determine a score that can be used to determine whether the sample belongs to the phenotype.
    • 通常,本发明应用将对照样品中的基因表达信号的概率分布转换为均匀分布的转化。 均匀分布可以更好地比较基因的表达水平。 转化源自对照数据的基因表达信号,并应用于表型数据的基因表达信号。 表型数据可以以矩阵格式表示。 可以确定将以表型为特征的许多基因表达模式(以子矩阵的形式)。 统一分配在这方面有所帮助,因为它可以更好地比较模式。 然后可以将基因表达模式用于将样品分类为属于表型集。 优选地,使用判别函数将样品与表征表型的基因表达模式进行比较。 判别函数可以确定可用于确定样本是否属于表型的分数。
    • 44. 发明申请
    • Characterization of Phenotypes by Gene Expression Patterns and Classification of Samples Based Thereon
    • 通过基因表达模式表征表型和样本分类
    • US20100023273A1
    • 2010-01-28
    • US12574195
    • 2009-10-06
    • Andrea CalifanoGustavo A. StolovitzkyYuhai Tu
    • Andrea CalifanoGustavo A. StolovitzkyYuhai Tu
    • G06F19/00
    • G06F19/24G06F19/20
    • Generally, the present invention applies a transformation to convert a probability distribution of gene expression signals in control samples to a uniform distribution. The uniform distribution allows better comparisons between expression levels for genes. The transformation is derived from gene expression signals of control data, and is applied to gene expression signals of phenotype data. The phenotype data can be represented in a matrix format. A number of gene expression patterns may be determined (in the form of submatrices) that will characterize the phenotype. The uniform distribution helps in this regard, as it allows better comparisons of patterns. The gene expression patterns can then be used to classify samples as belonging to the phenotype set. Preferably, a discriminant function is used to compare a sample with the gene expression patterns that characterize the phenotype. The discriminant function can determine a score that can be used to determine whether the sample belongs to the phenotype.
    • 通常,本发明应用将对照样品中的基因表达信号的概率分布转换为均匀分布的转化。 均匀分布可以更好地比较基因的表达水平。 转化源自对照数据的基因表达信号,并应用于表型数据的基因表达信号。 表型数据可以以矩阵格式表示。 可以确定将以表型为特征的许多基因表达模式(以子矩阵的形式)。 统一分配在这方面有所帮助,因为它可以更好地比较模式。 然后可以将基因表达模式用于将样品分类为属于表型集。 优选地,使用判别函数将样品与表征表型的基因表达模式进行比较。 判别函数可以确定可用于确定样本是否属于表型的分数。
    • 45. 发明授权
    • Tandem repeat detection using pattern discovery
    • 使用模式发现进行串联重复检测
    • US06446011B1
    • 2002-09-03
    • US09528601
    • 2000-03-20
    • Aris FloratosIsidore RigoutsosGustavo A. Stolovitzky
    • Aris FloratosIsidore RigoutsosGustavo A. Stolovitzky
    • G01N3348
    • G06F19/22G06F19/24Y10S707/99936
    • An algorithm which detects tandem repeats (TR) is provided. In an illustrative embodiment, a set of repeating units contained in an input sequence is identified, wherein each given repeating unit satisfies at least the following conditions: (a) a first measure of similarity between adjacent repeating units in the set is greater than a first user defined threshold, and (b) the given repeating unit includes at least one unit having a second measure of similarity with any other unit in the set that is a greater than a second user defined threshold. The method then provides for reporting positions in the input sequence that are covered by the set of repeating units.
    • 提供了一种检测串联重复(TR)的算法。 在说明性实施例中,识别包含在输入序列中的一组重复单元,其中每个给定的重复单元至少满足以下条件:(a)该组中相邻重复单元之间的相似度的第一测量值大于第一 用户定义的阈值,以及(b)所述给定的重复单元包括至少一个单元,所述至少一个单元具有与所述集合中的大于第二用户定义的阈值的任何其他单元的相似度的第二度量。 该方法然后提供在输入序列中报告由该组重复单元覆盖的位置。