Visant-Predictome: A System for Integration, Mining Visualization and Analysis

Visant-Predictome：集成、采矿可视化和分析系统

• 批准号: 7457647
• 负责人: CHARLES DELISI
• 金额: $ 43.79万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7457647
• 关键词: Address; Archives; Automobile Driving; Bayesian Method; Binding; Binding Sites; Biological; Cell physiology; Cellular Structures; Chemicals; Communication; Communities; Complex; Computer Systems Development; Computer software; Condition; Data; Data Sources; Databases; Dependence; Dependency; Development; Dictionary; Disease; Educational workshop; Electronic Mail; Facility Construction Funding Category; Genbank; Genes; Goals; Imagery; Information Systems; Link; Machine Learning; Maintenance; Methods; Mining; Modeling; Names; Network-based; Numbers; Online Mendelian Inheritance In Man; Phylogenetic Analysis; Proteomics; RNA Splicing; Reaction; Reporting; Score; Software Tools; Source; Structure; System; Systems Integration; Techniques; Technology; Tertiary Protein Structure; Update; Ursidae Family; Variant; Visual; Weight; base; chemical reaction; data mining; improved; models and simulation; open source; outreach; protein protein interaction; software development; statistics; tool; tool development; web-accessible; wiki

DESCRIPTION (provided by applicant): Recent and continuing technological advances are producing large amounts of disparate data about cell structure, function and activity. This is driving the development of tools for storing, mining, analyzing, visualizing and integrating data. This proposal describes the VisANT system: a tool for visual data mining that operates on a local database which includes results from our lab, as well as automatically updated proteomics data from web accessible databases such as MIPS and BIND. In addition to accessing its own database, a name normalization table (i.e. a dictionary of identifiers), permits the system to seamlessly retrieve sequence, disease and other data from sources such as GenBank and OMIM. The visualization tool is able to reversibly group related sets of nodes, and display and duplicate their internal structure, providing an approach to hierarchical representation and modeling. We propose to build further on these unique features by including capabilities for mining and representing chemical reactions, orthologous networks, combinatorially regulated transcriptional networks, splice variants and functional hierarchies. Software is open source, and the system also allows users to exchange and integrate the networks that they discover with those of others.

描述（由申请人提供）：最近和持续的技术进步正在产生大量关于细胞结构、功能和活性的不同数据。这推动了用于存储、挖掘、分析、可视化和集成数据的工具的开发。该提案描述了VisANT系统：一种可视化数据挖掘工具，可在本地数据库上运行，其中包括我们实验室的结果，以及来自MIPS和BIND等网络可访问数据库的自动更新的蛋白质组学数据。除了访问其自身的数据库之外，名称标准化表（即标识符字典）允许系统从诸如GenBank和OMIM的源无缝地检索序列、疾病和其他数据。该可视化工具能够可逆地对相关节点集进行分组，并显示和复制其内部结构，提供了一种分层表示和建模的方法。我们建议进一步建立在这些独特的功能，包括挖掘和代表化学反应，正交网络，组合调控的转录网络，剪接变体和功能层次结构的能力。软件是开源的，该系统还允许用户与其他人交换和集成他们发现的网络。