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    METHODS AND SYSTEMS FOR IDENTIFYING A DRUG MECHANISM OF ACTION USING NETWORK DYSREGULATION
    1.
    发明公开
    METHODS AND SYSTEMS FOR IDENTIFYING A DRUG MECHANISM OF ACTION USING NETWORK DYSREGULATION 审中-公开
    方法和系统用于识别药物的有效机制BY NETZWERKDYSREGULATION

    公开(公告)号：EP3140648A2

    公开(公告)日：2017-03-15

    申请号：EP15789337.1

    申请日：2015-05-11

    申请人： The Trustees of Columbia University in the City of New York

    发明人： CALIFANO, Andrea ,  BANSAL, Mukesh ,  SHIMONI, Yishai

    IPC分类号： G01N33/48 ,  G01N33/50 ,  G06F17/00

    CPC分类号： G06F19/702 ,  C40B30/02 ,  G06F19/12 ,  G06F19/24 ,  G06F19/703

    摘要： Techniques to identify a mechanism of action of a compound using network dysregulation are disclosed herein. An example method can include selecting at least a first interaction involving at least a first gene, determining a first n-dimensional probability density of gene expression levels for the first gene and one or more genes in a control state, determining a second n-dimensional probability density of gene expression levels for the first gene and one or more genes following treatment using at least one compound, estimating changes between the first probability density and the second probability density, and determining whether the estimated changes are statistically significant.

    摘要翻译： 技术来识别使用网络失调被盘在一个游离缺失化合物的作用的机构。 的示例性方法可以至少包括选择的第一交互至少涉及第一基因，确定性开采的第一个基因的基因表达水平和一个或更多个基因的一个控制状态的第一n维概率密度的，确定性的采矿第二n维 对于第一个基因的基因表达水平和一个或多个基因使用以下的至少一种化合物，无论是所估计的变化是统计学显著估计所述第一概率密度和第二概率密度，和确定性采矿之间的变化治疗概率密度。

    VIRTUAL INFERENCE OF PROTEIN ACTIVITY BY REGULON ENRICHMENT ANALYSIS
    2.
    发明公开
    VIRTUAL INFERENCE OF PROTEIN ACTIVITY BY REGULON ENRICHMENT ANALYSIS 审中-公开

    公开(公告)号：EP3341498A1

    公开(公告)日：2018-07-04

    申请号：EP16842702.9

    申请日：2016-08-26

    申请人： The Trustees of Columbia University in the City of New York

    发明人： ALVAREZ, Mariano, Javier ,  CALIFANO, Andrea

    IPC分类号： C12Q1/68 ,  G06F19/00 ,  G06F19/12

    CPC分类号： G06F19/18 ,  G06F19/12 ,  G06F19/20

    摘要： Methods for determining regulon enrichment in gene expression signatures are disclosed herein. An example method can include obtaining a set of transcriptional targets of a regulon. The method can include obtaining a gene expression signature by comparing a gene expression profile of a test sample to gene expression profiles of a plurality of samples representing control phenotypes. The method can include calculating a regulon enrichment score for each regulon in the gene expression signature. The method can including determining whether a number of control samples in the control phenotypes is above a predetermined threshold to support evaluation of statistical significance using permutation analysis. The method can include, in response to determining that the number of control samples is above the predetermined threshold, calculating a significance value by comparing each regulon enrichment score to a null model.