Sequence pattern descriptors for transmembrane structural details
    1.
    发明授权
    Sequence pattern descriptors for transmembrane structural details 有权
    跨膜结构细节的序列模式描述符

    公开(公告)号:US07991563B2

    公开(公告)日:2011-08-02

    申请号:US11852691

    申请日:2007-09-10

    IPC分类号: G01N33/48 G01N31/00 G06G7/48

    CPC分类号: G06F19/24 G06F19/16 G06F19/22

    摘要: The relationship between an amino acid sequence of a protein and its three-dimensional structure is at the very core of structural biology and bioinformatics. The occurrence and conservation of non-canonical conformations is a “local” phenomenon, i.e., non-canonical conformations are encoded intra-helically by short peptide sequences (heptapeptides at most). Effective descriptors can be formed for these short sequences employing training sets. Multiple, distinct patterns are created representing these sequences. A composite descriptor is formed by selecting from among the patterns discovered. The composite descriptor has a high level of sensitivity and specificity while, at the same time, a boosted signal-to-noise ratio.

    摘要翻译: 蛋白质的氨基酸序列与其三维结构之间的关系是结构生物学和生物信息学的核心。 非规范构象的发生和保守是“局部”现象,即非规范构象由短肽序列(最多七肽)螺旋内编码。 可以为采用训练集的这些短序列形成有效描述符。 创建表示这些序列的多个不同的模式。 通过从发现的模式中进行选择形成复合描述符。 复合描述符具有高水平的灵敏度和特异性,同时具有提升的信噪比。

    Sequence pattern descriptors for transmembrane structural details
    2.
    发明授权
    Sequence pattern descriptors for transmembrane structural details 失效
    跨膜结构细节的序列模式描述符

    公开(公告)号:US07698067B2

    公开(公告)日:2010-04-13

    申请号:US10305552

    申请日:2002-11-27

    IPC分类号: G01N33/48 G01N31/00 G06G7/48

    CPC分类号: G06F19/24 G06F19/16 G06F19/22

    摘要: The relationship between an amino acid sequence of a protein and its three-dimensional structure is at the very core of structural biology and bioinformatics. The occurrence and conservation of non-canonical conformations is a “local” phenomenon, i.e., non-canonical conformations are encoded intra-helically by short peptide sequences (heptapeptides at most). Effective descriptors can be formed for these short sequences employing training sets. Multiple, distinct patterns are created representing these sequences. A composite descriptor is formed by selecting from among the patterns discovered. The composite descriptor has a high level of sensitivity and specificity while, at the same time, a boosted signal-to-noise ratio.

    摘要翻译: 蛋白质的氨基酸序列与其三维结构之间的关系是结构生物学和生物信息学的核心。 非规范构象的发生和保守是“局部”现象,即非规范构象由短肽序列(最多七肽)螺旋内编码。 可以为采用训练集的这些短序列形成有效描述符。 创建表示这些序列的多个不同的模式。 通过从发现的模式中进行选择形成复合描述符。 复合描述符具有高水平的灵敏度和特异性,同时具有提升的信噪比。

    SEQUENCE PATTERN DESCRIPTORS FOR TRANSMEMBRANE STRUCTURAL DETAILS

    公开(公告)号:US20080171904A1

    公开(公告)日:2008-07-17

    申请号:US11852691

    申请日:2007-09-10

    IPC分类号: A61F5/58

    CPC分类号: G06F19/24 G06F19/16 G06F19/22

    摘要: The relationship between an amino acid sequence of a protein and its three-dimensional structure is at the very core of structural biology and bioinformatics. The occurrence and conservation of non-canonical conformations is a “local” phenomenon, i.e., non-canonical conformations are encoded intra-helically by short peptide sequences (heptapeptides at most). Effective descriptors can be formed for these short sequences employing training sets. Multiple, distinct patterns are created representing these sequences. A composite descriptor is formed by selecting from among the patterns discovered. The composite descriptor has a high level of sensitivity and specificity while, at the same time, a boosted signal-to-noise ratio.

    SEQUENCE PATTERN DESCRIPTORS FOR TRANSMEMBRANE STRUCTURAL DETAILS
    4.
    发明申请
    SEQUENCE PATTERN DESCRIPTORS FOR TRANSMEMBRANE STRUCTURAL DETAILS 失效
    用于变形结构细节的序列图描述

    公开(公告)号:US20080133142A1

    公开(公告)日:2008-06-05

    申请号:US11852671

    申请日:2007-09-10

    IPC分类号: G01N33/68

    CPC分类号: G06F19/24 G06F19/16 G06F19/22

    摘要: The relationship between an amino acid sequence of a protein and its three-dimensional structure is at the very core of structural biology and bioinformatics. The occurrence and conservation of non-canonical conformations is a “local” phenomenon, i.e., non-canonical conformations are encoded intra-helically by short peptide sequences (heptapeptides at most). Effective descriptors can be formed for these short sequences employing training sets. Multiple, distinct patterns are created representing these sequences. A composite descriptor is formed by selecting from among the patterns discovered. The composite descriptor has a high level of sensitivity and specificity while, at the same time, a boosted signal-to-noise ratio.

    摘要翻译: 蛋白质的氨基酸序列与其三维结构之间的关系是结构生物学和生物信息学的核心。 非规范构象的发生和保守是“局部”现象,即非规范构象由短肽序列(最多七肽)螺旋内编码。 可以为采用训练集的这些短序列形成有效描述符。 创建表示这些序列的多个不同的模式。 通过从发现的模式中进行选择形成复合描述符。 复合描述符具有高水平的灵敏度和特异性,同时具有提升的信噪比。