公开(公告)号：US20060050946A1

公开(公告)日：2006-03-09

申请号：US10435827

申请日：2003-05-12

Applicant: Timothy Mitchison ,  Steven Altschuler ,  Yan Feng ,  Thomas Mayer ,  Zachary Perlman ,  Michael Slack ,  Lani Wu

Inventor： Timothy Mitchison ,  Steven Altschuler ,  Yan Feng ,  Thomas Mayer ,  Zachary Perlman ,  Michael Slack ,  Lani Wu

IPC: G06K9/00

CPC classification number: G06K9/0014 ,  G06T7/0012 ,  G06T2207/30024

Abstract: The present invention provides methods and systems for automated morphological analysis of cells. The inventive methods are particularly useful in the rapid analysis of cells required in a biological screen. Agents which cause a particular phenotype in the cells can be identified using the inventive quantitative morphometric analysis of cells. The data gathered using the inventive method can also be quantified and analyzed later for various trends and classifications. Characteristics of cells which can be determined using this method include number of nuclei, size of cell, size of nuclei, number of the centrosomes, shape of cells, size of centrosomes, perimeter of nucleus, shape of nucleus, pattern of staining, and degree of staining.

Abstract translation: 本发明提供了用于细胞自动形态学分析的方法和系统。 本发明的方法在生物屏幕中所需的细胞的快速分析中特别有用。 可以使用本发明的细胞定量形态学分析来鉴定在细胞中引起特定表型的药剂。 使用本发明方法收集的数据也可以针对各种趋势和分类进行量化和分析。 可以使用该方法确定的细胞的特征包括细胞核的数量，细胞的大小，细胞核的大小，中心体的数量，细胞的形状，中心体的大小，细胞核的周长，细胞核的形状，染色的图案和程度 的染色。

公开(公告)号：US06556983B1

公开(公告)日：2003-04-29

申请号：US09481615

申请日：2000-01-12

Applicant: Steven Altschuler ,  David V. Ingerman ,  Lani Wu ,  Lei Zhao

Inventor： Steven Altschuler ,  David V. Ingerman ,  Lani Wu ,  Lei Zhao

IPC: G06F1700

CPC classification number: G06F17/30958 ,  G06F17/30997 ,  G06K9/6296

Abstract: A pattern lattice data space as a framework for analyzing data, in which both schema-based and statistical analysis are accommodated, is defined. Ways to manage the size of the lattice structures in the pattern lattice data space are described. Utilities to classify or cluster, search (find similar data), or relate data using lattice fragments in the pattern lattice data space are also described. Superpattern cone or lattice generation function, which may be used by the classification and clustering functions, is also described. In addition, a subpattern cone or lattice generation process, which may be used by the search (find similar data) and data relating functions, is also described. Finally, a function to label, in readily understandable “pidgin”, categories which classify information, is also described.

Abstract translation: 定义了一种模式格数据空间作为分析数据的框架，其中包含基于模式和统计分析的框架。 描述了在图案格子数据空间中管理格子结构尺寸的方法。 还描述了在图案格子数据空间中分类或聚类，搜索（找到相似数据）或使用格子片段关联数据的实用程序。 还描述了可以由分类和聚类功能使用的超模式锥或格子生成函数。 此外，还描述了可以通过搜索（查找相似数据）和数据相关功能使用的子模式锥或格子生成处理。 最后，还描述了一种易于理解的“pidgin”类别对信息进行分类的标签的功能。

公开(公告)号：US20050091042A1

公开(公告)日：2005-04-28

申请号：US10992051

申请日：2004-11-18

Applicant: Alejandro Acero ,  Steven Altschuler ,  Lani Wu

Inventor： Alejandro Acero ,  Steven Altschuler ,  Lani Wu

IPC: G10L11/02 ,  G10L21/02 ,  H04R3/00

CPC classification number: G10L25/78 ,  G10L21/0264 ,  G10L2021/02082 ,  G10L2021/02161

Abstract: Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.

公开(公告)号：US20060154236A1

公开(公告)日：2006-07-13

申请号：US11271215

申请日：2005-11-11

Applicant: Steven Altschuler ,  Lani Wu ,  Michael Slack

Inventor： Steven Altschuler ,  Lani Wu ,  Michael Slack

IPC: C12Q1/00 ,  G06F19/00

CPC classification number: G01N33/5026

Abstract: The present invention provides methods and systems for automated morphological analysis of cells also known as phenotypic screening. The inventive methods are particularly useful in the rapid analysis of cells required in a biological screen or in the screening for agents with a particular mechanism of action. Agents which cause a particular phenotype in the cells can be identified using the inventive quantitative morphometric analysis of cells. The data gathered using the inventive method can also be quantified and analyzed later for various trends and classifications (e.g., Kolmogorov-Smirnov statistics, titration-invariant similarity scores). Characteristics of cells which can be determined using this method include number of nuclei, size of cell, size of nuclei, number of the centrosomes, shape of cells, size of centrosomes, perimeter of nucleus, shape of nucleus, staining for a particular protein, staining for an organelle, pattern of staining, and degree of staining.

Abstract translation: 本发明提供了也称为表型筛选的细胞的自动形态学分析的方法和系统。 本发明的方法在生物屏幕中所需的细胞的快速分析或具有特定作用机制的试剂的筛选中特别有用。 可以使用本发明的细胞定量形态学分析来鉴定在细胞中引起特定表型的药剂。 使用本发明方法收集的数据也可以针对各种趋势和分类进行量化和分析（例如，Kolmogorov-Smirnov统计，滴定 - 不变相似性评分）。 可以使用该方法确定的细胞的特征包括细胞核的数量，细胞的大小，细胞核的大小，中心体的数量，细胞的形状，中心体的大小，细胞核的周长，细胞核的形状，特定蛋白质的染色， 染色细胞器，染色图案和染色程度。