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1. 发明申请

US20130246033A1 PREDICTING PHENOTYPES OF A LIVING BEING IN REAL-TIME 审中-公开
标题翻译：实时预测生活中的阴谋
公开(公告)号：US20130246033A1
公开(公告)日：2013-09-19
申请号：US13419439
申请日：2012-03-14
申请人： David Earl Heckerman , Jennifer Listgarten , Carl M. Kadie , Omer Weissbrod
发明人： David Earl Heckerman , Jennifer Listgarten , Carl M. Kadie , Omer Weissbrod
IPC分类号： G06G7/60
CPC分类号： G16B20/00 , G16B40/00
摘要： Described herein are technologies pertaining to predicting whether a living being, such as a human being, an animal, or a plant, has a phenotype or set of phenotypes in real-time or near real-time. A filter set of genetic markers are determined heuristically, by first univariately computing scores for respective genetic markers that are indicative of their predictive ability with respect to the phenotype or the set of phenotypes. Thereafter, during training, the filter set is initially selected and thereafter expanded based upon the scores, until predictive accuracy for the phenotype or set of phenotypes reaches a threshold or is optimized. The filter set, which includes a relatively small number of genetic markers, is subsequently employed for real-time or near-real time phenotype prediction.
摘要翻译：这里描述的是关于预测诸如人类，动物或植物的生物是否具有实时或接近实时的表型或一组表型的技术。初步确定遗传标记的过滤器集合，首先单个计算相应遗传标记的分数，这些评估指示其相对于表型或一组表型的预测能力。此后，在训练期间，最初选择过滤器组，然后基于分数进行扩展，直到表型或一组表型的预测精度达到阈值或被优化为止。随后将包括相对较少数量的遗传标记的滤器组用于实时或近实时表型预测。

2. 发明申请

US20130246017A1 COMPUTING PARAMETERS OF A PREDICTIVE MODEL 审中-公开
标题翻译：预测模型的计算参数
公开(公告)号：US20130246017A1
公开(公告)日：2013-09-19
申请号：US13549527
申请日：2012-07-16
申请人： David Earl Heckerman , Jennifer Listgarten , Carl M. Kadie , Omer Weissbrod
发明人： David Earl Heckerman , Jennifer Listgarten , Carl M. Kadie , Omer Weissbrod
IPC分类号： G06F17/10
CPC分类号： G06K9/6278 , H04L51/12
摘要： A computer-executable algorithm that estimates parameters of a predictive model in computation time of less than O(n2k2) when k
摘要翻译：本文描述了当k <= n时估计小于O（n2k2）的计算时间中的预测模型的参数的计算机可执行算法，其中n是在估计预测模型的参数时考虑的数量项数， k是在估计预测模型的参数时考虑的每个数据项的多个特征。在给定训练数据中考虑的特征的情况下，估计这些参数最大化训练数据中观察目标值的概率。

3. 发明申请

US20100191513A1 REFINING HLA DATA 有权
标题翻译：修改HLA数据
公开(公告)号：US20100191513A1
公开(公告)日：2010-07-29
申请号：US12431786
申请日：2009-04-29
申请人： Jennifer Listgarten , David Earl Heckerman , Carl M. Kadie
发明人： Jennifer Listgarten , David Earl Heckerman , Carl M. Kadie
IPC分类号： G06F17/10 , G06F17/18
CPC分类号： G06F19/18 , G06F19/24
摘要： A system described herein includes a receiver component that receives an HLA data set, wherein the HLA data set comprises low resolution HLA data. An HLA refinement component comprises a statistical model that automatically refines the HLA data set to transform the low resolution HLA data to high resolution HLA data.
摘要翻译：本文描述的系统包括接收HLA数据集的接收器组件，其中HLA数据集包括低分辨率HLA数据。 HLA细化组件包括自动细化HLA数据集以将低分辨率HLA数据转换为高分辨率HLA数据的统计模型。

4. 发明申请

US20140066320A1 IDENTIFYING CAUSAL GENETIC MARKERS FOR A SPECIFIED PHENOTYPE 审中-公开
标题翻译：鉴定指定基因的原始基因标记
公开(公告)号：US20140066320A1
公开(公告)日：2014-03-06
申请号：US13603403
申请日：2012-09-04
申请人： David Earl Heckerman , Jennifer Listgarten , Christoph Anthony Lippert , Jing Xiang , Nicolo Fusi , Carl M. Kadie , Robert I. Davidson
发明人： David Earl Heckerman , Jennifer Listgarten , Christoph Anthony Lippert , Jing Xiang , Nicolo Fusi , Carl M. Kadie , Robert I. Davidson
IPC分类号： C40B30/02
CPC分类号： G16B20/00 , G16B40/00
摘要： Described herein are technologies pertaining to computationally-efficiently performing genome-wide association studies. Feature selection methods are used to identify genetic markers for addressing potential confounding in the data. Then, single SNPs, or groups of genetic markers are analyzed to ascertain whether such groups are causal or tagging of causal as to a specified phenotype, after taking in to account the feature-selected SNPs. Group and univariate analysis is accomplished by way of analyzing a group of genetic markers conditioned upon other genetic markers that are found to be predictive of the specified phenotype.
摘要翻译：这里描述的是涉及计算上有效执行全基因组关联研究的技术。特征选择方法用于识别用于解决数据中潜在混淆的遗传标记。然后分析单核苷酸多态性（SNPs）或遗传标记物组，以确定这些群体在考虑特征选择的单核苷酸多态性之后，是否因为特定表型的因果性或标记因素。组和单变量分析是通过分析一组基于其他遗传标记的遗传标记来实现的，这些遗传标记被发现是预测指定的表型。

5. 发明授权

US08473218B2 Refining HLA data 有权
标题翻译：精炼HLA数据
公开(公告)号：US08473218B2
公开(公告)日：2013-06-25
申请号：US12431786
申请日：2009-04-29
申请人： Jennifer Listgarten , David Earl Heckerman , Carl M. Kadie
发明人： Jennifer Listgarten , David Earl Heckerman , Carl M. Kadie
IPC分类号： G01N33/50
CPC分类号： G06F19/18 , G06F19/24
摘要： A system described herein includes a receiver component that receives an HLA data set, wherein the HLA data set comprises low resolution HLA data. An HLA refinement component comprises a statistical model that automatically refines the HLA data set to transform the low resolution HLA data to high resolution HLA data.
摘要翻译：本文描述的系统包括接收HLA数据集的接收器组件，其中HLA数据集包括低分辨率HLA数据。 HLA细化组件包括自动细化HLA数据集以将低分辨率HLA数据转换为高分辨率HLA数据的统计模型。

6. 发明授权

US07953738B2 System and method for visualization of categories 有权
标题翻译：类别可视化的系统和方法
公开(公告)号：US07953738B2
公开(公告)日：2011-05-31
申请号：US10955585
申请日：2004-09-30
申请人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
发明人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
IPC分类号： G06F17/30
CPC分类号： G06T11/206 , G06F17/30256 , G06F17/30259 , G06F17/30265 , Y10S707/917 , Y10S707/99945
摘要： Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.
摘要翻译：提供了类别的分布显示，其显示了类别中所有情况下的连续属性的分布，并且提供了分类属性的不同状态的总体的直方图。可以提供由属性（在一个维度）和类别（在另一维度中）的这种显示器的数组。还提供类别图显示，用于可视化不同类别及其分布，人口和相似之处。这些通过不同的节点和边缘的阴影显示，表示类别和两个类别之间的关系，以及通过节点的接近。

7. 发明授权

US06807537B1 Mixtures of Bayesian networks 失效
标题翻译：贝叶斯网络的混合
公开(公告)号：US06807537B1
公开(公告)日：2004-10-19
申请号：US08985114
申请日：1997-12-04
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
IPC分类号： G06N302
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choices made among a sample of users and the hidden variables to be the preferences of those users.
摘要翻译：本发明的一个方面是构建贝叶斯网络的混合物。本发明的另一方面是使用贝叶斯网络的这种混合来执行推理。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数，并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。在本发明的一种模式中，选择具有最高MBN分数的MBN用于执行推定。在本发明的另一模式中，一些或所有MBN被保留为并行执行推论的MBN的集合，其输出根据相应的MBN分数加权，并且MBN收集输出是所有MBN的加权和输出。在本发明的一个应用中，可以通过将观察到的变量定义为在用户样本中作出的选择和作为这些用户的偏好的隐藏变量来执行协同过滤。

8. 发明授权

US09495775B2 System and method for visualization of categories 有权
标题翻译：类别可视化的系统和方法
公开(公告)号：US09495775B2
公开(公告)日：2016-11-15
申请号：US10955738
申请日：2004-09-30
申请人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
发明人： David Maxwell Chickering , Zhaohui Tang , David Earl Heckerman , Robert L. Rounthwaite , Alexei V. Bocharov , Scott Conrad Oveson
IPC分类号： G06T11/20 , G06F17/30
CPC分类号： G06T11/206 , G06F17/30256 , G06F17/30259 , G06F17/30265 , Y10S707/917 , Y10S707/99945
摘要： Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.
摘要翻译：提供了类别的分布显示，其显示了类别中所有情况下的连续属性的分布，并且提供了分类属性的不同状态的总体的直方图。可以提供由属性（在一个维度）和类别（在另一维度中）的这种显示器的数组。还提供类别图显示，用于可视化不同类别及其分布，人口和相似之处。这些通过不同的节点和边缘的阴影显示，表示类别和两个类别之间的关系，以及通过节点的接近。

9. 发明申请

US20110300226A1 PEPTIDE PARTICLE FORMULATION 有权
标题翻译：肽颗粒配方
公开(公告)号：US20110300226A1
公开(公告)日：2011-12-08
申请号：US13153826
申请日：2011-06-06
申请人： Reid M. RUBSAMEN , David Earl Heckerman
发明人： Reid M. RUBSAMEN , David Earl Heckerman
IPC分类号： A61K9/14 , A61P37/04 , A61K39/00
CPC分类号： A61K39/385 , A61K9/1647 , A61K9/5153 , A61K39/245 , A61K39/39 , A61K2039/55511 , A61K2039/55555 , A61K2039/55572 , A61K2039/57 , A61K2039/6093 , A61K2039/70 , C12N7/00 , C12N2710/16134
摘要： A composition as disclosed is comprised of a plurality of groups of particles. The particles are comprised of a biocompatible polymer which maybe a co-polymer such as PLGA combined with a peptide of a sequence of interest, e.g. a sequence which corresponds to a sequence presented on a surface of a cell infected with a virus. A plurality of different groups of particles are provided in the formulation wherein the particles within any single group include peptides of identical amino acid sequence. The particles are sized such that they are sufficiently large so as to prevent more than the contents of a single particle from being presented to a single immune system cell.
摘要翻译：所公开的组合物由多组颗粒组成。颗粒由生物相容性聚合物组成，其可以是共聚物，例如与感兴趣的序列的肽结合的PLGA，例如。对应于在感染病毒的细胞表面上呈现的序列的序列。在制剂中提供多个不同组的颗粒，其中任何单一组中的颗粒包括相同氨基酸序列的肽。这些颗粒的尺寸使得它们足够大，以便防止单个颗粒的含量超过单个免疫系统细胞。

10. 发明授权

US06496816B1 Collaborative filtering with mixtures of bayesian networks 有权
标题翻译：使用贝叶斯网络混合进行协同过滤
公开(公告)号：US06496816B1
公开(公告)日：2002-12-17
申请号：US09220199
申请日：1998-12-23
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
IPC分类号： G06N302
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choices made among a sample of users and the hidden variables to be the preferences of those users.
摘要翻译：本发明的一个方面是构建贝叶斯网络的混合物。本发明的另一方面是使用贝叶斯网络的这种混合来执行推理。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数，并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。在本发明的一种模式中，选择具有最高MBN分数的MBN用于执行推定。在本发明的另一模式中，一些或所有MBN被保留为并行执行推论的MBN的集合，其输出根据相应的MBN分数加权，并且MBN收集输出是所有MBN的加权和输出。在本发明的一个应用中，可以通过将观察到的变量定义为在用户样本中作出的选择和作为这些用户的偏好的隐藏变量来执行协同过滤。

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