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    • 2. 发明授权
    • Database system for predictive cellular bioinformatics
    • 用于预测细胞生物信息学的数据库系统
    • US06615141B1
    • 2003-09-02
    • US09718704
    • 2000-11-21
    • James H. SabryCynthia L. AdamsEugeni A. VaisbergAnne M. Crompton
    • James H. SabryCynthia L. AdamsEugeni A. VaisbergAnne M. Crompton
    • G01N3348
    • G06K9/00127C12M41/36C12M41/46G06F19/24G06T7/0012G06T2207/30024Y10S707/99933Y10S707/99934Y10S707/99936
    • A system for acquiring knowledge from cellular information. The system has a database comprising a database management module (“DBMS”). The system also has a variety of modules, including a population module coupled to the DBMS for categorizing and storing a plurality of features (e.g., cell size, distance between cells, cell population, cell type) from an image acquisition device into the database. The system has a translation module coupled to the DBMS for defining a descriptor from a set of selected features from the plurality of features. In a specific embodiment, the descriptor is for a known or unknown compound, e.g., drug. A prediction module is coupled to the DBMS for selecting one of a plurality of a descriptors from known and unknown compounds from the database based upon a selected descriptor from a selected compound. The selected compound may be one that is useful for treatment of human beings or the like.
    • 用于从蜂窝信息获取知识的系统。 该系统具有包括数据库管理模块(“DBMS”)的数据库。 该系统还具有各种模块,包括耦合到DBMS的群模块,用于从图像采集设备将多个特征(例如,小区大小,小区之间的距离,小区群,小区类型)分类和存储到数据库中。 该系统具有耦合到DBMS的翻译模块,用于从多个特征的一组选定特征中定义描述符。 在具体实施方案中,描述符是用于已知或未知的化合物,例如药物。 预测模块耦合到DBMS,用于基于来自所选化合物的所选择的描述符从数据库中选择来自已知和未知化合物的多个描述符之一。 所选择的化合物可以是可用于治疗人类等的化合物。
    • 4. 发明授权
    • Database system for predictive cellular bioinformatics
    • 用于预测细胞生物信息学的数据库系统
    • US06743576B1
    • 2004-06-01
    • US09311890
    • 1999-05-14
    • James H. SabryCynthia L. AdamsEugeni A. VaisbergAnne M. Crompton
    • James H. SabryCynthia L. AdamsEugeni A. VaisbergAnne M. Crompton
    • C12Q100
    • G06K9/00127C12M41/36C12M41/46G06F19/24G06T7/0012G06T2207/30024Y10S707/99933Y10S707/99934Y10S707/99936
    • A system for acquiring knowledge from cellular information. The system has a database comprising a database management module (“DBMS”). The system also has a variety of modules, including a population module coupled to the DBMS for categorizing and storing a plurality of features (e.g., cell size, distance between cells, cell population, cell type) from an image acquisition device into the database. The system has a translation module coupled to the DBMS for defining a descriptor from a set of selected features from the plurality of features. In a specific embodiment, the descriptor is for a known or unknown compound, e.g., drug. A prediction module is coupled to the DBMS for selecting one of a plurality of a descriptors from known and unknown compounds from the database based upon a selected descriptor from a selected compound. The selected compound may be one that is useful for treatment of human beings or the like.
    • 用于从蜂窝信息获取知识的系统。 该系统具有包括数据库管理模块(“DBMS”)的数据库。 该系统还具有各种模块,包括耦合到DBMS的群模块,用于从图像采集设备将多个特征(例如,小区大小,小区之间的距离,小区群,小区类型)分类和存储到数据库中。 该系统具有耦合到DBMS的翻译模块,用于从多个特征的一组选定特征中定义描述符。 在具体实施方案中,描述符是用于已知或未知的化合物,例如药物。 预测模块耦合到DBMS,用于基于来自所选化合物的所选择的描述符从数据库中选择来自已知和未知化合物的多个描述符之一。 所选择的化合物可以是可用于治疗人类等的化合物。
    • 6. 发明授权
    • Characterizing biological stimuli by response curves
    • 通过响应曲线表征生物刺激
    • US07657076B2
    • 2010-02-02
    • US11186143
    • 2005-07-20
    • Eugeni A. VaisbergDonald R. OestreicherCynthia L. Adams
    • Eugeni A. VaisbergDonald R. OestreicherCynthia L. Adams
    • G06K9/00G06K9/20G06K9/36G06F19/00
    • G06K9/6253G06F19/70G06K9/00127
    • A method for generating stimulus response curves (e.g., dose response curves) shows how the phenotype of one or more cells change in response to varying levels of the stimulus. Each “point” on the curve represents quantitative phenotype for cell(s) at a particular level of stimulus (e.g., dose of a therapeutic). The quantitative phenotypes are multivariate phenotypic representations of the cell(s). They include various features of the cell(s) obtained by image analysis. Such features often include basic parameters obtained from images (e.g., cell shape, nucleus area, Golgi texture) and/or biological characterizations derived from the basic parameters (e.g., cell cycle state, mitotic index, etc.). The stimulus response curves may be compared to allow classification of stimuli and identify subtle differences in related stimuli. To facilitate the comparison, it may be desirable to present the response curves in a principal component space.
    • 用于产生刺激响应曲线(例如,剂量反应曲线)的方法示出了一种或多种细胞的表型如何响应于刺激的不同水平而改变。 曲线上的每个“点”表示在特定刺激水平(例如治疗剂的剂量)下的细胞的定量表型。 定量表型是细胞的多变量表型表达。 它们包括通过图像分析获得的细胞的各种特征。 这些特征通常包括从基本参数(例如细胞周期状态,有丝分裂指数等)导出的图像(例如,细胞形状,细胞核区域,高尔基体织构)和/或生物学表征获得的基本参数。 可以比较刺激反应曲线以允许刺激分类并识别相​​关刺激的微妙差异。 为了便于比较,可能期望在主要分量空间中呈现响应曲线。