itNETZ: Integrative and Translational Network-based Cellular Signature Analyzer

itNETZ：基于集成和翻译网络的细胞特征分析仪

• 批准号: 8462869
• 负责人: Chung-Che Chang
• 金额: $ 6万
• 依托单位: METHODIST HOSPITAL RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-24 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8462869
• 关键词: Address; Cell Line; Cell physiology; Cells; Classification; Clinical; Collaborations; Communities; Computer Analysis; Computer software; Data; Data Analyses; Diffusion; Disease; Drug Delivery Systems; Education; Ensure; Extensible Markup Language; Future; Gene Expression Profile; Gene Mutation; Generations; Genes; Genomics; Goals; Graph; Hybrids; Imagery; Internet; Knowledge; Libraries; Life; Ligands; Maps; Mass Spectrum Analysis; Metric; Modeling; Molecular; Mutation; Nature; Network-based; Output; Pathway interactions; Pharmaceutical Preparations; Phase; Phenotype; Phosphoproteins; Physicians; Process; Proteomics; Protocols documentation; Public Health; Research; Resources; Screening procedure; Signal Pathway; Signal Transduction; Source; System; Therapeutic; Training Programs; Training Support; Tumor Biology; Work; base; cell behavior; cell type; cellular imaging; computerized data processing; data exchange; data format; data integration; data mining; data modeling; design; drug candidate; drug mechanism; high throughput screening; image processing; in vivo; inhibitor/antagonist; insight; interest; mathematical model; medical specialties; novel; novel strategies; programs; receptor; relational database; response; tool; vector

DESCRIPTION (provided by applicant): There is an urgent need to develop systematic platforms to address the challenges and opportunities brought forth by the fast progresses of the Library of Integrated Network-Based Cellular Signatures (LINCS) program. The LINCS program performs cross-cutting high-throughput assays and develops integrative computational analysis of informative molecular activity and cellular feature signatures generated in response to a variety of perturbing agents and drug candidates. The primary goal of the proposed study is to address the needs by developing a signature-oriented software platform, the Integrative and Translational Network-based Cellular Signature Analyzer (itNETZ). The working flow of the system is: 1) to identify disease- and drug-specific molecular and cellular features, 2) to reveal the mechanismistic associations between components of such features and delineate them as signaling and regulating networks, 3) to present the dynamics of such networks by mathematical models, 4) to construct network-based molecular and cellular signatures, 5) to discover common signatures and networks across cell lines and diseases, 6) to establish and maintain a public resource of the increasing resultant knowledge of therapeutic responses, and 7) to facilitate the research community on querying signatures of interests, exploring correlations among signatures, and generating hypotheses. This system will enable the following functions: first, the basic analysis and discovery toolkits for processing cellular images, Luminex genomics data, transcriptome sequencing data, and for modeling phosphoproteins signaling pathway; and second, data integration and mining toolkits for mapping genomics and proteomics to cellular phenotypes, for core pathway signature identification on cell lines treated by different inhibitors and drug-induced pathway signature alterations, and for constructing drug kinome landscapes. The itNETZ system comprises pipelines that load input, analyze images, process genomics and proteomics data, export outputs into a relational database, integrate and mine the data, and generate network-based cellular signatures of interest. XML-based protocols will be used for data exchanging.

描述（由申请人提供）：迫切需要开发系统平台来应对基于集成网络的蜂窝签名库（LINCS）项目的快速发展所带来的挑战和机遇。LINCS项目执行跨领域的高通量分析，并开发信息分子活性和细胞特征特征的综合计算分析，以响应各种干扰剂和候选药物。提出的研究的主要目标是通过开发一个面向签名的软件平台，即基于集成和转换网络的蜂窝签名分析仪（itNETZ）来满足需求。系统的工作流程为：1)识别疾病和药物特异性分子和细胞特征，2)揭示这些特征组成部分之间的机制关联，并将它们描述为信号和调节网络，3)通过数学模型呈现这些网络的动力学，4)构建基于网络的分子和细胞特征，5)发现细胞系和疾病之间的共同特征和网络，6)建立和维护一个不断增加的治疗反应结果知识的公共资源，7)促进研究界查询兴趣特征，探索特征之间的相关性，并产生假设。该系统将实现以下功能：首先，用于处理细胞图像、Luminex基因组数据、转录组测序数据和磷酸化蛋白信号通路建模的基本分析和发现工具包；其次，数据整合和挖掘工具，用于基因组学和蛋白质组学到细胞表型的映射，用于在不同抑制剂处理和药物诱导的途径信号改变的细胞系上进行核心途径信号识别，以及构建药物激酶组景观。itNETZ系统包括加载输入、分析图像、处理基因组学和蛋白质组学数据、将输出输出输出到关系数据库、整合和挖掘数据以及生成感兴趣的基于网络的细胞特征的管道。基于xml的协议将用于数据交换。