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1. 发明申请

WO2004003683A2 CONFORMATIONAL SAMPLING BY SELF-ORGANIZATION 审中-公开
标题翻译：通过自组织进行构形抽样
公开(公告)号：WO2004003683A2
公开(公告)日：2004-01-08
申请号：PCT/US0319905
申请日：2003-06-26
申请人： DIMENSIONAL PHARM INC , AGRAFIOTIS DIMITRIS K , XU HUAFENG , IZRAILEV SERGEI F , SALEMME FRANCIS R
发明人： AGRAFIOTIS DIMITRIS K , XU HUAFENG , IZRAILEV SERGEI F , SALEMME FRANCIS R
IPC分类号： G01N33/48 , G06F20060101 , G06F19/00 , G06F19/16 , G06F
CPC分类号： G06F19/701
摘要： A self-organizing method, system, and computer program product for generating molecular conformations that are consistent with a set of distance and/or volume constraints. A stochastic proximity embedding (SPE) algorithm evaluates individual distance and/or volume constraints and adjusts the atomic coordinates to minimize violations of such constraints. The method scales linearly with thenumber of atoms, and produces many more unique conformations at a fraction of the time required by conventional distance geometry algorithms.
摘要翻译：用于产生与一组距离和/或体积限制一致的分子构象的自组织方法，系统和计算机程序产品。随机接近嵌入（SPE）算法评估个体距离和/或体积约束，并调整原子坐标以最小化违反这些约束。该方法随原子数量线性变化，并在常规距离几何算法所需时间的一小部分时间内产生更多独特构象。

2. 发明申请

WO02061419A9 METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR ANALYZING COMBINATORIAL LIBRARIES 审中-公开
标题翻译：用于分析组合图书馆的方法，系统和计算机程序产品
公开(公告)号：WO02061419A9
公开(公告)日：2002-10-31
申请号：PCT/US0202369
申请日：2002-01-29
申请人： DIMENSIONAL PHARM INC , AGRAFIOTIS DIMITRIS K , LOBANOV VICTOR S , SALEMME FRANCIS R
发明人： AGRAFIOTIS DIMITRIS K , LOBANOV VICTOR S , SALEMME FRANCIS R
IPC分类号： G06F15/18 , G06N3/02 , G01N33/48
CPC分类号： G06N3/02 , B01J2219/00686 , B01J2219/00689 , B01J2219/00695 , B01J2219/007 , B01J2219/00702 , B01J2219/0072 , C40B50/02 , G06F19/707 , G06N99/005 , Y10S707/99943
摘要： The invention provides for in silico analysis of a virtual combinatorial library. Mapping coordinates for a training subset of products in the combinatorial library, and features of their building blocks, are obtained. A supervised machine learning approach is used to infer a mapping function f that transforms the building block features for each product in the training subset of products to the corresponding mapping coordinates for each product in the training subset of products. The mapping function f is then encoded in a computer readable medium. The mapping function f can be retrieved and used to generate mapping coordinates for any product in the combinatorial library from the building block features associated with the product.
摘要翻译：本发明提供了虚拟组合库的计算机分析。获得组合库中产品训练子集的映射坐标，以及它们的构建块的特征。监督机器学习方法用于推断将产品训练子集中的每个产品的构建块特征变换成产品训练子集中的每个产品的对应映射坐标的映射函数f i。然后将映射函数f i编码在计算机可读介质中。映射函数可以被检索并用于从与产品相关联的构建块特征中的组合库中的任何产品生成映射坐标。

3. 发明申请

WO0225504A3 METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR ENCODING AND BUILDING PRODUCTS OF A VIRTUAL COMBINATORIAL LIBRARY 审中-公开
标题翻译：一种虚拟组合库的编码和构建产品的方法，系统和计算机程序产品
公开(公告)号：WO0225504A3
公开(公告)日：2002-10-17
申请号：PCT/US0129140
申请日：2001-09-20
申请人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
发明人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
IPC分类号： B01J19/00 , C07B61/00 , C07K1/04 , C40B50/02 , G06F17/30 , G06F19/00
CPC分类号： C40B50/02 , B01J19/0046 , B01J2219/00689 , B01J2219/00695 , B01J2219/007 , B01J2219/0072 , C07K1/047 , C40B40/00
摘要： The present invention provides a method, system, and computer program product for encoding and building products of a virtual combinatorial library. A chemical reaction and reagent data for forming products of the virtual combinatorial library are encoded in a computer readable form. A compiler then operates on the encoded information and generates reagent mapping data. The compiler compiles the encoded chemical reaction to generate computer instructions that control the operation of a processor. A compact data structure containing data is generated and stored in a memory. This data structure is then used to gain immediate access to any of the products of the virtual combinatorial library.
摘要翻译：本发明提供了用于编码和构建虚拟组合库的产品的方法，系统和计算机程序产品。用于形成虚拟组合文库的产品的化学反应和试剂数据以计算机可读形式编码。然后编译器对编码信息进行操作并生成试剂映射数据。编译器编译编码的化学反应以生成控制处理器操作的计算机指令。包含数据的紧凑数据结构被生成并存储在存储器中。然后使用该数据结构立即访问虚拟组合库的任何产品。

4. 发明专利

AU9274001A Method, system, and computer program product for encoding and building products of a virtual combinatorial library 未知
公开(公告)号：AU9274001A
公开(公告)日：2002-04-02
申请号：AU9274001
申请日：2001-09-20
申请人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
发明人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
IPC分类号： B01J19/00 , C07B61/00 , C07K1/04 , C40B50/02 , G06F17/30 , G06F19/00 , G06F17/50
摘要： The present invention provides a method, system, and computer program product for encoding and building products of a virtual combinatorial library. A chemical reaction and reagent data for forming products of the virtual combinatorial library are encoded in a computer readable form. A compiler then operates on the encoded information and generates reagent mapping data. The compiler compiles the encoded chemical reaction to genenerate computer instructions that control the operation of a processor. A compact data structure containing data is generated and stored in a memory. This data structure is then used to gain immediate access to any of the products of the virtual combinatorial library.

5. 发明专利

AU8660101A Method, system, and computer program product for determining properties of combinatorial library products from features of library building blocks 未知
公开(公告)号：AU8660101A
公开(公告)日：2002-03-04
申请号：AU8660101
申请日：2001-08-22
申请人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
发明人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
IPC分类号： G06F17/50 , G06F15/18 , G06N3/02
摘要： The present invention determines properties of combinatorial library products from features of library building blocks. At least one feature is determined for each building block of a combinatorial library having a plurality of products. A training subset of products is selected from the products, and at least one property is determined for each product of the training subset. A building block set is identified for each product of the training subset, and an input features vector is formed from the features of the identified building blocks for each product of the training subset. A supervised machine learning approach is used to infer a mapping function that transforms the input features vector for each product of the training subset to the corresponding at least one property for each product of the training subset. After the mapping function is inferred, it is used for determining properties of other products of the library from their corresponding input features vectors.

6. 发明申请

WO0171624A9 SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR REPRESENTING OBJECT RELATIONSHIPS IN A MULTIDIMENSIONAL SPACE 审中-公开
标题翻译：用于表示多维空间中对象关系的系统，方法和计算机程序产品
公开(公告)号：WO0171624A9
公开(公告)日：2003-01-30
申请号：PCT/US0108974
申请日：2001-03-22
申请人： DIMENSIONAL PHARM INC , AGRAFIOTIS DIMITRIS K , RASSOKHIN DMITRII N , LOBANOV VICTOR S , SALEMME F RAYMOND
发明人： AGRAFIOTIS DIMITRIS K , RASSOKHIN DMITRII N , LOBANOV VICTOR S , SALEMME F RAYMOND
IPC分类号： G06F15/18 , G06K9/62 , G06Q10/00 , G06N3/04
CPC分类号： G06Q10/10 , G06K9/6232 , G06K9/6253 , G06N99/005
摘要： A method and computer product is presented for mapping n-dimensional input patterns into an m-dimensional space so as to preserve relationships that may exist in the n-dimensional space. A subsetof the input patterns is chosen and mapped into the m-dimensionalspace using an iterative nonlinear mapping process. A set of locally defined neural networks is created, then trained in accordance with the mapping produced by the iterative process. Additional input patterns not in the subset are mapped into the m-dimensional space by using one of the local neural networks. In an alternative embodiment, the local neural networks are only used after training and use of a global neural network. The global neural network is trained in accordance with the mapping produced by the iterative process. Input patterns are initially projected into the m-dimensional space using the global neural network. Local neural networks are then used to refine the results of the global network.
摘要翻译：提出了一种方法和计算机产品，用于将n维输入模式映射到m维空间，以便保留可能存在于n维空间中的关系。使用迭代非线性映射过程来选择输入模式的下划线并映射到m维空间。创建一组本地定义的神经网络，然后根据迭代过程产生的映射进行训练。通过使用局部神经网络之一，不在子集中的附加输入模式被映射到m维空间。在替代实施例中，局部神经网络仅在训练和使用全局神经网络之后使用。全局神经网络根据迭代过程产生的映射进行训练。输入模式最初使用全局神经网络投射到m维空间中。然后使用局部神经网络来改进全局网络的结果。

7. 发明申请

WO9820437A3 SYSTEM, METHOD AND COMPUTER PROGRAM PRODUCT FOR IDENTIFYING CHEMICAL COMPOUNDS HAVING DESIRED PROPERTIES 审中-公开
标题翻译：用于识别具有所需特性的化学化合物的系统，方法和计算机程序产品
公开(公告)号：WO9820437A3
公开(公告)日：1998-06-25
申请号：PCT/US9720918
申请日：1997-11-04
申请人： DIMENSIONAL PHARM INC
发明人： AGRAFIOTIS DIMITRIS K , BONE ROGER F , SALEMME FRANCIS R , SOLL RICHARD M
IPC分类号： G01N33/00 , B01J19/00 , C07B61/00 , G01N33/15 , G06F15/18 , G06F17/30 , G06F17/50 , G06F19/00 , G06F19/16 , G06F19/26 , G06N3/00 , G06T11/20 , G06T17/40
CPC分类号： G06T11/206 , B01J19/0046 , B01J2219/00689 , B01J2219/00691 , B01J2219/00695 , B01J2219/007 , B01J2219/00702 , C40B40/00 , G06F19/707 , G06F19/708 , G06K9/6251 , G06K9/6253
摘要： An automatic, partially automatic, and/or manual iterative system, method and/or computer program product for generating chemical entities having desired or specified physical, chemical, functional, and/or bioactive properties. The present invention identifies a set of compounds for analysis; collects, acquires or synthesizes the identified compounds; analyzes the compounds to determine one or more physical, chemical and/or bioactive properties (structure-property data); and uses the structure-property data to identify another set of compounds for analysis in the next iteration. An Experiment Planner generates Selection Criteria and/or one or more Objective Functions for use by a Selector. The Selector searches the Compound Library to identify a subset of compounds (a Directed Diversity Library) that maximizes or minimizes the Objective Functions. The compounds listed in the Directed Diversity Library are then collected, acquired or synthesized, and are analyzed to evaluate their properties of interest. In one embodiment, when a compound in a Directed Diversity Library is available in a Chemical Inventory, the compound is retrieved from the Chemical Inventory instead of re-synthesizing the compound.

8. 发明申请

WO0217149A8 METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR DETERMINING PROPERTIES OF COMBINATORIAL LIBRARY PRODUCTS FROM FEATURES OF LIBRARY BUILDING BLOCKS 审中-公开
标题翻译：用于确定组合库产品性质的方法，系统和计算机程序产品从图书馆建筑块的特征确定
公开(公告)号：WO0217149A8
公开(公告)日：2003-09-04
申请号：PCT/US0126144
申请日：2001-08-22
申请人： DIMENSIONAL PHARM INC
发明人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
IPC分类号： G06F17/50 , G06F15/18 , G06N3/02 , G06F19/00
CPC分类号： G06N99/005 , B01J2219/00686 , B01J2219/00689 , B01J2219/00695 , B01J2219/007 , B01J2219/00702 , B01J2219/0072 , G06N3/02
摘要： The present invention determines properties of combinatorial library products from features of library building blocks. At least one feature is determined for each building block of a combinatorial library having a plurality of products. A training subset of products is selected from the products, and at least one property is determined for each product of the training subset. A building block set is identified for each product of the training subset, and an input features vector is formed from the features of the identified building blocks for each product of the training subset. A supervised machine learning approach is used to infer a mapping function that transforms the input features vector for each product of the training subset to the corresponding at least one property for each product of the training subset. After the mapping function is inferred, it is used for determining properties of other products of the library from their corresponding input features vectors.
摘要翻译：本发明从文库构建块的特征确定组合文库产物的性质。为具有多个产品的组合库的每个构建块确定至少一个特征。从产品中选择产品的培训子集，并且为培训子集的每个产品确定至少一个属性。针对训练子集的每个产品识别构件块组，并且针对训练子集的每个产品从识别的构件块的特征形成输入特征向量。使用受监督的机器学习方法来推导映射函数，该映射函数将训练子集的每个乘积的输入特征矢量变换为用于训练子集的每个乘积的相应的至少一个特性。推断映射函数后，它用于从其对应的输入特征向量确定库的其他产品的属性。

9. 发明申请

WO0165462A3 METHOD AND COMPUTER PROGRAM PRODUCT FOR DESIGNING COMBINATORIAL ARRAYS 审中-公开
标题翻译：用于设计组合阵列的方法和计算机程序产品
公开(公告)号：WO0165462A3
公开(公告)日：2002-03-07
申请号：PCT/US0106217
申请日：2001-02-28
申请人： DIMENSIONAL PHARM INC
发明人： AGRAFIOTIS DIMITRIS K , LOBANOV VICTOR S , SALEMME FRANCIS RAYMOND
IPC分类号： G01N33/00 , G01N33/48 , G01N33/50 , G01N33/53 , G06F19/00 , G11C17/00
CPC分类号： C40B50/02
摘要： A greedy method for designing combinatorial arrays. An array of reagents are initially selected from a list of candidate reagents in a combinatorial library. The reagents in the array that maximize a design objective are determined in an iterative manner, by examining each variation site in the combinatorial library in a strictly alternating sequence. During each step, each candidate reagent at a given variation site is evaluated by constructing and evaluating the sub-array resulting from the systematic combination of that reagent with the selected reagents at all the other variation sites in the library. The candidate reagents at that variation site are ranked according to the fitness of their respective sub-arrays, and the reagents with the highest fitness are selected. The process is repeated for each variation site in the combinatorial library, until the fitness of the full combinatorial array can no longer be improved.
摘要翻译：一种设计组合阵列的贪心方法。最初从组合库中的候选试剂列表中选出一组试剂。通过以严格交替的顺序检查组合库中的每个变异位点，以迭代的方式确定最大化设计目标的阵列中的试剂。在每个步骤中，通过构建和评估由该试剂与所选择的试剂在文库中的所有其它变体位点的系统组合产生的子阵列来评估给定变体位点处的每种候选试剂。根据其各个子阵列的适合度对该变异位点处的候选试剂进行排序，并选择具有最高适应度的试剂。对组合库中的每个变异位点重复该过程，直到完全组合阵列的适应度不能再被改善。

10. 发明申请

WO0217149A3 METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR DETERMINING PROPERTIES OF COMBINATORIAL LIBRARY PRODUCTS FROM FEATURES OF LIBRARY BUILDING BLOCKS 审中-公开
标题翻译：方法，系统和计算机程序产品，用于从图书馆建筑块的特征确定组合图书馆产品的性质
公开(公告)号：WO0217149A3
公开(公告)日：2003-07-24
申请号：PCT/US0126144
申请日：2001-08-22
申请人： DIMENSIONAL PHARM INC
发明人： LOBANOV VICTOR S , AGRAFIOTIS DIMITRIS K , SALEMME FRANCIS R
IPC分类号： G06F17/50 , G06F15/18 , G06N3/02 , G06F19/00
CPC分类号： G06N99/005 , B01J2219/00686 , B01J2219/00689 , B01J2219/00695 , B01J2219/007 , B01J2219/00702 , B01J2219/0072 , G06N3/02
摘要： The present invention determines properties of combinatorial library products from features of library building blocks. At least one feature is determined for each building block of a combinatorial library having a plurality of products. A training subset of products is selected from the products, and at least one property is determined for each product of the training subset. A building block set is identified for each product of the training subset, and an input features vector is formed from the features of the identified building blocks for each product of the training subset. A supervised machine learning approach is used to infer a mapping function that transforms the input features vector for each product of the training subset to the corresponding at least one property for each product of the training subset. After the mapping function is inferred, it is used for determining properties of other products of the library from their corresponding input features vectors.
摘要翻译：本发明根据图书馆构件的特征确定组合图书馆产品的特性。为具有多个产品的组合库的每个构建块确定至少一个特征。从产品中选择产品的训练子集，并确定训练子集的每个产品的至少一个属性。为训练子集的每个乘积识别构建块集合，并且从训练子集的每个乘积的所识别的构建块的特征形成输入特征向量。监督机器学习方法被用于推断映射函数，该映射函数将训练子集的每个乘积的输入特征向量变换为训练子集的每个乘积的对应的至少一个属性。在推测出映射函数之后，它用于从其相应的输入特征向量确定库的其他产品的属性。

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