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1.发明授权Method of determining a reliability indicator for signatures obtained from clinical data and use of the reliability indicator for favoring one signature over the other 有权确定从临床数据获得的签名的可靠性指标的方法，以及使用可靠性指标以有利于一个签名公开(公告)号：US08762072B2
公开(公告)日：2014-06-24
申请号：US13119742
申请日：2009-09-24
摘要： This invention relates to a method and an apparatus for determining a reliability indicator for at least one set of signatures obtained from clinical data collected from a group of samples. The signatures are obtained by detecting characteristics in the clinical data from the group of sample sand each of the signatures generate a first set of stratification values that stratify the group of samples. At least one additional and parallel stratification source to the signatures obtained from group of sample sis provided, the at least one additional and parallel stratification source to the signatures being independent from the signatures and generates a second set of stratification values. A comparison is done for each respective sample, where the first stratification values are compared with a true reference stratification values, and where the second stratification values are compared with the true reference stratification values. The signatures are assigned with similarity measure indicators indicating whether the first and the second stratification values match with the true reference stratification values. These are then implementing as input in determining the reliability of the signatures.
摘要翻译： 本发明涉及一种用于确定从从一组样本收集的临床数据中获得的至少一组签名的可靠性指标的方法和装置。 通过检测来自样品组的临床数据的特征来获得这些特征，每个签名产生分层样本的第一组分层值。 至少一个附加和平行分层源提供从样本组提供的签名，所述签名的至少一个附加和平行分层源独立于签名并产生第二组分层值。 对每个相应的样本进行比较，其中将第一分层值与真实的参考分层值进行比较，并且将第二分层值与真实的参考分层值进行比较。 赋予签名的相似性度量指示符指示第一和第二分层值是否与真实的参考分层值相匹配。 然后在确定签名的可靠性时，将其作为输入。
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公开(公告)号：US20140040264A1
公开(公告)日：2014-02-06
申请号：US13983651
申请日：2012-01-30
申请人： Vinay Varadan , Prateek Mittal , Sitharthan Kamalakaran , Nevenka Dimitrova , Angel Janevski , Nilanjana Banerjee
发明人： Vinay Varadan , Prateek Mittal , Sitharthan Kamalakaran , Nevenka Dimitrova , Angel Janevski , Nilanjana Banerjee
IPC分类号： G06F19/00
CPC分类号： G06F19/324 , G16B5/00 , G16B25/00 , G16B40/00
摘要： The present invention relates to a method for stratifying a patient into a clinically relevant group comprising the identification of the probability of an alteration within one or more sets of molecular data from a patient sample in comparison to a database of molecular data of known phenotypes, the inference of the activity of a biological network on the basis of the probabilities, the identification of a network information flow probability for the patient via the probability of interactions in the network, the creation of multiple instances of network information flow for the patient sample and the calculation of the distance of the patient from other subjects in a patient database using multiple instances of the network information flow. The invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy wherein the biomedical marker or group of biomedical markers comprises altered biological pathway markers, as well as to an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer. Furthermore, a corresponding clinical decision support system is provided.
摘要翻译： 本发明涉及一种用于将患者分层为临床相关组的方法，其包括鉴定来自患者样品的一组或多组分子数据内的改变概率与已知表型的分子数据的数据库相比较， 基于概率推断生物网络的活动，通过网络中的交互概率识别患者的网络信息流概率，创建患者样本的多个网络信息流实例和 使用网络信息流的多个实例来计算患者与患者数据库中的其他受试者的距离。 本发明进一步涉及生物医学标记物或生物医学标记物组，其与受试者对癌症治疗的响应性的高可能性相关联，其中生物医学标记物或生物医学标记物组包括改变的生物学途径标志物，以及用于检测 ，诊断，毕业，监测或预测医学状况，或用于检测，诊断，监测或预测受试者对于针对所述医学病症，特别是卵巢癌的治疗的反应性。 此外，提供了相应的临床决策支持系统。
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公开(公告)号：US10340027B2
公开(公告)日：2019-07-02
申请号：US13877346
申请日：2011-10-04
申请人： Nilanjana Banerjee , Angel Janevski , Sitharthan Kamalakaran , Vinay Varadan , Nevenka Dimitrova , Robert Lucito
发明人： Nilanjana Banerjee , Angel Janevski , Sitharthan Kamalakaran , Vinay Varadan , Nevenka Dimitrova , Robert Lucito
摘要： The present invention relates to a method for identifying multi-modal associations between biomedical markers which allows for the determination of network nodes and/or high ranking network members or combinations thereof, indicative of having a diagnostic, prognostic or predictive value for a medical condition, in particular ovarian cancer. The present invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy, preferably a platinum based cancer therapy, wherein said biomedical marker or group of biomedical markers comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 8, 19, 20 or all markers selected from PKMYT1, SKIL, RAB8A, HIRIP3, CTNNB1, NGFR, ZCCHC11, LSP1, CD200, PAX8, CYBRD1, HOXC11, TCEAL1, FZD10, FZD1, BBS4, IRS2, TLX3, TSPAN2, TXN, and CFLAR. Furthermore, an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, 1 diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer, is provided, as well as a corresponding method for classifying a subject comprising and a medical decision support system.
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公开(公告)号：US20120265446A1
公开(公告)日：2012-10-18
申请号：US13321723
申请日：2010-05-18
IPC分类号： G06F19/00
摘要： A method (10) for forming novel signatures of biological data is provided. The method comprises ranking features based on a trend value, which is created based on multiple signatures identified by a pattern discovery method. Furthermore, a device (30) and a computer program product (40), performing the steps according to the method (10) is provided. Uses of the method, for statistically analyzing clinical data, designing assays based on multiple molecular signatures and interpreting assays based on multiple molecular signatures are also provided.
摘要翻译： 提供了一种用于形成生物数据新特征的方法（10）。 该方法包括基于基于由模式发现方法识别的多个签名创建的趋势值对特征进行排序。 此外，提供了执行根据方法（10）的步骤的设备（30）和计算机程序产品（40）。 还提供了该方法的用途，用于统计分析临床数据，基于多个分子特征设计测定和基于多个分子特征的解释测定。
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5.发明申请公开(公告)号：US20130196877A1
公开(公告)日：2013-08-01
申请号：US13877346
申请日：2011-10-04
申请人： Nilanjana Banerjee , Angel Janevski , Sitharthan Kamalakaran , Vinay Varadan , Nevenka Dimitrova , Robert Lucito
发明人： Nilanjana Banerjee , Angel Janevski , Sitharthan Kamalakaran , Vinay Varadan , Nevenka Dimitrova , Robert Lucito
IPC分类号： G06F19/20
摘要： The present invention relates to a method for identifying multi-modal associations between biomedical markers which allows for the determination of network nodes and/or high ranking network members or combinations thereof, indicative of having a diagnostic, prognostic or predictive value for a medical condition, in particular ovarian cancer. The present invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy, preferably a platinum based cancer therapy, wherein said bio-medical marker or group of biomedical markers comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 8, 19, 20 or all markers selected from PKMYT1, SKIL, RAB8A, HIRIP3, CTNNB1, NGFR, ZCCHC11, LSP1, CD200, PAX8, CYBRD1, HOXC11, TCEAL1, FZD10,FZD1, BBS4, IRS2, TLX3, TSPAN2, TXN, and CFLAR. Furthermore, an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, 1 diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer, is provided, as well as a corresponding method for classifying a subject comprising and a medical decision support system.
摘要翻译： 本发明涉及一种用于识别生物医学标记之间的多模式关联的方法，其允许确定网络节点和/或高排名网络成员或其组合，指示具有用于医疗状况的诊断，预后或预测值， 特别是卵巢癌。 本发明还涉及与受试者对癌症治疗（优选基于铂的癌症治疗）的高反应性的高可能性相关联的生物医学标记物或生物医学标记物组，其中所述生物医学标记物或生物医学标记物组至少包括 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,8,19,20或选自PKMYT1，SKIL，RAB8A， HIRIP3，CTNNB1，NGFR，ZCCHC11，LSP1，CD200，PAX8，CYBRD1，HOXC11，TCEAL1，FZD10，FZD1，BBS4，IRS2，TLX3，TSPAN2，TXN和CFLAR。 此外，提供了用于检测，诊断，毕业，监测或预测医学状况或用于检测1诊断，监测或预测受试者对于针对所述医学病症，特别是卵巢癌的治疗的反应性的测定法，作为 以及用于分类受试者的相应方法以及医疗决策支持系统。
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6.发明申请METHOD OF DETERMINING A RELIABILITY INDICATOR FOR SIGNATURES OBTAINED FROM CLINICAL DATA AND USE OF THE RELIABILITY INDICATOR FOR FAVORING ONE SIGNATURE OVER THE OTHER 有权确定从临床数据中获取的标志的可靠性指标的方法和使用可靠性指标，以便在其他人身上获得一个签名公开(公告)号：US20110173201A1
公开(公告)日：2011-07-14
申请号：US13119742
申请日：2009-09-24
IPC分类号： G06F17/30
摘要： This invention relates to a method and an apparatus for determining a reliability indicator for at least one set of signatures obtained from clinical data collected from a group of samples. The signatures are obtained by detecting characteristics in the clinical data from the group of sample sand each of the signatures generate a first set of stratification values that stratify the group of samples. At least one additional and parallel stratification source to the signatures obtained from group of sample sis provided, the at least one additional and parallel stratification source to the signatures being independent from the signatures and generates a second set of stratification values. A comparison is done for each respective sample, where the first stratification values are compared with a true reference stratification values, and where the second stratification values are compared with the true reference stratification values. The signatures are assigned with similarity measure indicators indicating whether the first and the second stratification values match with the true reference stratification values. These are then implementing as input in determining the reliability of the signatures.
摘要翻译： 本发明涉及一种用于确定从从一组样本收集的临床数据中获得的至少一组签名的可靠性指标的方法和装置。 通过检测来自样品组的临床数据的特征来获得这些特征，每个签名产生分层样本的第一组分层值。 至少一个附加和平行分层源提供从样本组提供的签名，所述签名的至少一个附加和平行分层源独立于签名并产生第二组分层值。 对每个相应的样本进行比较，其中将第一分层值与真实的参考分层值进行比较，并且将第二分层值与真实的参考分层值进行比较。 赋予签名的相似性度量指示符指示第一和第二分层值是否与真实的参考分层值相匹配。 然后在确定签名的可靠性时，将其作为输入。
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公开(公告)号：US11348662B2
公开(公告)日：2022-05-31
申请号：US13321723
申请日：2010-05-18
摘要： A method (10) for forming novel signatures of biological data is provided. The method comprises ranking features based on a trend value, which is created based on multiple signatures identified by a pattern discovery method. Furthermore, a device (30) and a computer program product (40), performing the steps according to the method (10) is provided. Uses of the method, for statistically analyzing clinical data, designing assays based on multiple molecular signatures and interpreting assays based on multiple molecular signatures are also provided.
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8.发明申请INTEGRATED ACCESS TO AND INTERATION WITH MULTIPLICITY OF CLINICA DATA ANALYTIC MODULES 审中-公开综合访问和与临床数据分析模块的多重性相关联公开(公告)号：US20130282404A1
公开(公告)日：2013-10-24
申请号：US13976170
申请日：2012-01-04
申请人： Angel Janevski , Sitharthan Kamalakaran , Christian Reichelt , Nilanjana Banerjee , Vinay Varadan , Nevenka Dimitrova
发明人： Angel Janevski , Sitharthan Kamalakaran , Christian Reichelt , Nilanjana Banerjee , Vinay Varadan , Nevenka Dimitrova
IPC分类号： G06F19/00
CPC分类号： G16H50/70 , G06F19/325 , G16H40/63
摘要： A state machine (22) stores a current state (30) comprising a clinical context defined by available patient-related information relating to a medical patient, and identifies one or more available analytical tools of a set of analytical tools (24) that are applicable to the current state. A graphical user interface module (16) receives a user selection of an available analytical tool. The state machine loads patient-related information (40) to the user-selected available analytical tool (24sel) and invokes the user-selected available analytical tool to operate on the loaded patient-related information to generate additional patient-related information relating to the medical patient and/or graphical patient-related content relating to the medical patient. The state machine transitions from the current state (30) to a next state (30′) and/or invokes the graphical user interface module to display the graphical patient related content.
摘要翻译： 状态机（22）存储当前状态（30），其包括由与医疗患者有关的可用患者相关信息定义的临床上下文，并且识别可应用的一组分析工具（24）中的一个或多个可用分析工具 到目前状态。 图形用户界面模块（16）接收可用分析工具的用户选择。 状态机将患者相关信息（40）加载到用户选择的可用分析工具（24sel），并且调用用户选择的可用分析工具对所加载的患者相关信息进行操作，以生成与患者相关的附加信息 与患者有关的医疗病人和/或图形患者相关内容。 状态机从当前状态（30）转换到下一状态（30'）和/或调用图形用户界面模块以显示图形的患者相关内容。
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公开(公告)号：US09858392B2
公开(公告)日：2018-01-02
申请号：US12992169
申请日：2009-05-06
申请人： Angel J. Janevski , Nevenka Dimitrova , Sitharthan Kamalakaran , Yasser Alsafadi , Nilanjana Banerjee , Anca Ioana Daniela Bacur , Jasper Van Leeuwen , Vinay Varadan
发明人： Angel J. Janevski , Nevenka Dimitrova , Sitharthan Kamalakaran , Yasser Alsafadi , Nilanjana Banerjee , Anca Ioana Daniela Bacur , Jasper Van Leeuwen , Vinay Varadan
摘要： The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.
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公开(公告)号：US20130102483A1
公开(公告)日：2013-04-25
申请号：US13641282
申请日：2011-04-08
申请人： Nevenka Dimitrova , Surabhi Khandige , Satyamoorthy Kapaettu , Aparna Gorthi , Shama Prasada Kabekkodu , Sanjiban Chakrabarty , Payal Keswarpu , Nilanjana Banerjee , Angel Janevski , Prashantha Hebbar
发明人： Nevenka Dimitrova , Surabhi Khandige , Satyamoorthy Kapaettu , Aparna Gorthi , Shama Prasada Kabekkodu , Sanjiban Chakrabarty , Payal Keswarpu , Nilanjana Banerjee , Angel Janevski , Prashantha Hebbar
IPC分类号： C12Q1/68
CPC分类号： C12Q1/6886 , C12Q2600/112 , C12Q2600/154
摘要： The present invention relates to methods, arrays and computer programs for assisting in classifying breast cancer diseases. In particular the invention relates to classifying breast cancer disorders by determining the methylation status of one or more sequences according to SEQ ID NO: 1-111. The classification may be further strengthened by also taking the expression levels of one or more proteins into account.
摘要翻译： 本发明涉及用于辅助乳腺癌疾病分类的方法，阵列和计算机程序。 特别地，本发明涉及通过确定根据SEQ ID NO：1-111的一个或多个序列的甲基化状态来分类乳腺癌病症。 考虑到一种或多种蛋白质的表达水平，可以进一步加强分类。
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