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    • 21. 发明申请
    • System and method for integrating and validating genotypic, phenotypic and medical information into a database according to a standardized ontology
    • 根据标准化本体将基因型,表型和医学信息整合并验证成数据库的系统和方法
    • US20070178501A1
    • 2007-08-02
    • US11634550
    • 2006-12-06
    • Matthew RabinowitzJonathan SheenaZachary DemkoChristopher ClarkNigam Shah
    • Matthew RabinowitzJonathan SheenaZachary DemkoChristopher ClarkNigam Shah
    • C12Q1/68G06F19/00G06Q50/00
    • G06Q50/22G06Q50/24
    • The system described herein enables clinicians and researchers to use aggregated genetic and phenotypic data from clinical trials and medical records to make the safest, most effective treatment decisions for each patient. This involves (i) the creation of a standardized ontology for genetic, phenotypic, clinical, pharmacokinetic, pharmacodynamic and other data sets, (ii) the creation of a translation engine to integrate heterogeneous data sets into a database using the standardized ontology, and (iii) the development of statistical methods to perform data validation and outcome prediction with the integrated data. The system is designed to interface with patient electronic medical records (EMRs) in hospitals and laboratories to extract a particular patient's relevant data. The system may also be used in the context of generating phenotypic predictions and enhanced medical laboratory reports for treating clinicians. The system may also be used in the context of leveraging the huge amount of data created in medical and pharmaceutical clinical trials. The ontology and validation rules are designed to be flexible so as to accommodate a disparate set of clients. The system is also designed to be flexible so that it can change to accommodate scientific progress and remain optimally configured.
    • 本文描述的系统使临床医师和研究人员能够使用来自临床试验和医疗记录的综合遗传和表型数据,为每位患者做出最安全,最有效的治疗决定。 这涉及(i)为遗传,表型,临床,药代动力学,药效学和其他数据集创建标准化本体,(ii)创建翻译引擎以将异构数据集合集成到使用标准化本体的数据库中,以及( iii)开发统计方法,使用综合数据进行数据验证和结果预测。 该系统旨在与医院和实验室中的患者电子病历(EMR)进行接口,以提取特定患者的相关数据。 该系统也可用于产生表型预测和增强的用于治疗临床医师的医学实验室报告。 该系统也可以在利用在医疗和药物临床试验中创造的大量数据的背景下使用。 本体和验证规则被设计为灵活的,以容纳不同的客户端集合。 该系统还被设计为灵活的,以便它可以改变以适应科学进步并保持最佳配置。
    • 22. 发明申请
    • METHODS FOR CELL GENOTYPING
    • 细胞基因分析方法
    • US20110033862A1
    • 2011-02-10
    • US12918445
    • 2009-02-19
    • Matthew RabinowitzDavid S. JohnsonJohan BanerZachary DemkoCengiz Cinnioglu
    • Matthew RabinowitzDavid S. JohnsonJohan BanerZachary DemkoCengiz Cinnioglu
    • C12Q1/68C12P19/34
    • C12Q1/6876C12Q2600/156C12Q2600/16C12Q2600/172
    • Methods for cell genotyping are disclosed herein. A method for determining the genomic data of one or a small number of cells, or from fragmentary DNA, where a limited quantity of genetic data is available may include adding one or more targeted primers to a whole genome amplification of a cell, increasing the accuracy with which key alleles are measured in the context of a whole genome amplification. The genetic material from a single cell may be divided into fractions, each of which may be separately genotyped, allowing the reconstruction of the cells haplotype. The genetic material from a single cell may be divided into fractions, each of which may be separately genotyped, and the distribution of the various alleles in the different fractions may be used to determine the ploidy state of one or a plurality of chromosomes in the cell.
    • 本文公开了细胞基因分型的方法。 用于确定有限数量的遗传数据可用的一个或少数细胞或来自片段DNA的基因组数据的方法可包括向细胞的全基因组扩增添加一种或多种靶向引物,增加细胞的准确度 在全基因组扩增的情况下测量关键等位基因。 来自单个细胞的遗传物质可以被分成各自的部分,每一个可以分开进行基因分型,允许重建细胞单元型。 来自单个细胞的遗传物质可以分成各自的部分,每个可以分别进行基因分型,并且可以使用不同级分中各种等位基因的分布来确定细胞中一条或多条染色体的倍性状态 。
    • 25. 发明授权
    • Method and system for training dynamic nonlinear adaptive filters which have embedded memory
    • 用于训练具有嵌入式存储器的动态非线性自适应滤波器的方法和系统
    • US06351740B1
    • 2002-02-26
    • US09201927
    • 1998-12-01
    • Matthew Rabinowitz
    • Matthew Rabinowitz
    • G06F1518
    • G06N99/005H03H21/0016H03H2222/04
    • Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.
    • 这里描述了一种用于训练具有嵌入式存储器的非线性自适应滤波器(或神经网络)的方法和系统。 这种存储器可以出现在多层有限脉冲响应(FIR)架构或无限脉冲响应(IIR)架构中。 我们专注于具有单独的线性动态组件和静态非线性组件的滤波器架构。 这样的滤波器可以被构造成基于关于待仿真的动态操作的先验知识来限制它们的计算自由度。 该方法对于由线性FIR滤波器和非线性广义单层子网组成的FIR架构是详细的。 对于IIR案例,我们将方法扩展到使用反馈的一般非线性架构。 对于这些动态架构,我们描述了如何应用优化技术,使更新更接近牛顿方向,而不是最速下降方法,如反向传播。 我们详细介绍了一种新颖的自适应修正高斯牛顿优化技术,它利用自适应学习速率来确定更新步长的幅度和方向。 对于广泛的自适应滤波应用,新的训练算法比最快下降方法(如反向传播通过时间和标准准牛顿法)收敛速度更快,成本更低。 我们应用算法建模非线性动态跟踪系统5的逆,以及非线性放大器6。
    • 28. 发明授权
    • ATSC transmitter identifier signaling
    • ATSC发射机标识符信令
    • US07792156B1
    • 2010-09-07
    • US12351841
    • 2009-01-11
    • Andy LeeJames J. Spilker, Jr.Matthew Rabinowitz
    • Andy LeeJames J. Spilker, Jr.Matthew Rabinowitz
    • H04J3/06
    • H04J13/105H04H60/50H04H60/52H04J13/0029H04J13/0048
    • Apparatus having corresponding computer programs comprise: a code generator adapted to generate a transmitter identification block, wherein the transmitter identification block comprises 32 rows and 82 columns, wherein the first 66 symbols in each of the rows comprises a cyclically-extended 63-chip pseudonoise code that is selectively polarity-inverted according to a respective phase of a 32-chip Walsh code, and wherein each of the last 16 columns comprises a parity-extended 31-chip Gold code that is selectively polarity-inverted according to a respective phase of a 16-chip Walsh code; and a code inserter adapted to insert each of the rows into the reserved block of a respective one of 32 consecutive field synchronization segments in an Advanced Television Systems Committee (ATSC) television signal prior to transmission of the ATSC television signal.
    • 具有对应的计算机程序的装置包括:适于产生发射机识别块的码发生器,其中发射机标识块包括32行和82列,其中每行中的前66个符号包括循环扩展的63码片伪噪声码 其根据32芯片沃尔什码的相应的相位被选择性地极性反转,并且其中最后16列中的每一列包括奇偶校验扩展的31芯片Gold码,其根据相应的相位被选择性地极性反转 16芯片沃尔什码; 以及代码插入器,其适于在传输ATSC电视信号之前将每个行插入高级电视系统委员会(ATSC)电视信号中的32个连续的场同步段中的相应一个的保留块。