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    • 4. 发明授权
    • Visualization and processing of multidimensional data using prefiltering and sorting criteria
    • 使用预过滤和排序标准可视化和处理多维数据
    • US06834122B2
    • 2004-12-21
    • US09767595
    • 2001-01-22
    • Mary M. YangEdward J. BylinaWilliam J. ColemanMichael R. DilworthSteven J. RoblesDouglas C. Youvan
    • Mary M. YangEdward J. BylinaWilliam J. ColemanMichael R. DilworthSteven J. RoblesDouglas C. Youvan
    • G06K968
    • G06K9/00127G06K9/0014G06K9/0063G06K9/6253G06K2009/00644G06K2009/4657G06T7/0012G06T2200/24G06T2207/10016G06T2207/10056G06T2207/30024Y10S128/922Y10S707/99937
    • Complex multidimensional datasets generated by digital imaging spectroscopy can be organized and analyzed by applying software and computer-based methods comprising sorting algorithms. Combinations of these algorithms to images and graphical data, allow pixels or features to be rapidly and efficiently classified into meaningful groups according to defined criteria. Multiple rounds of pixel or feature selection may be performed based on independent sorting criteria. In one embodiment sorting by spectral criteria (e.g., intensity at a given wavelength) is combined with sorting by temporal criteria (e.g., absorbance at a given time) to identify microcolonies of recombinant organisms harboring mutated genes encoding enzymes having desirable kinetic attributes and substrate specificity. Restriction of the set of pixels analyzed in a subsequent sort based on criteria applied in an earlier sort (“sort and lock” analyses) minimize computational and storage resources. User-defined criteria can also be incorporated into the sorting process by means of a graphical user interface that comprises a visualization tools including a contour plot, a sorting bar and a grouping bar, an image window, and a plot window that allow run-time interactive identification of pixels or features meeting one or more criteria, and display of their associated spectral or kinetic data. These methods are useful for extracting information from imaging data in applications ranging from biology and medicine to remote sensing.
    • 通过数字成像光谱法生成的复杂多维数据集可以通过应用软件和基于计算机的方法进行组织和分析,包括排序算法。 这些算法与图像和图形数据的组合允许像素或特征根据定义的标准快速有效地分类为有意义的组。 可以基于独立排序标准来执行多轮像素或特征选择。 在一个实施方案中,通过光谱标准(例如,给定波长处的强度)的排序与通过时间标准(例如,给定时间的吸光度)排序相结合,以鉴定携带突变基因的重组体的微菌落,所述突变基因编码具有期望的动力学属性和底物特异性的酶 。 基于先前排序(“排序和锁定”分析)中应用的标准,在后续排序中分析的像素集合的限制最小化了计算和存储资源。 用户定义的标准也可以通过包括可视化工具的图形用户界面结合到分类过程中,该可视化工具包括轮廓图,分类栏和分组条,图像窗口和允许运行时间的绘图窗口 满足一个或多个标准的像素或特征的交互式识别,以及它们相关联的光谱或动力学数据的显示。 这些方法可用于从生物学和医学到遥感等应用中从成像数据中提取信息。