Integrative Meta-analysis of Microarray Data

微阵列数据的综合荟萃分析

• 批准号: 7742635
• 负责人: PAUL PAVLIDIS
• 金额: $ 20.76万
• 依托单位: UNIVERSITY OF BRITISH COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2011-09-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7742635
• 关键词: Access to Information; Address; Algorithms; Area; Autopsy; Binding; Biology; Brain; Categories; Cereals; Clinical; Collection; Complex; Controlled Vocabulary; Data; Data Analyses; Data Set; Databases; Descriptor; Detection; Disease; Future; Gene Expression; Gene Targeting; Genes; Genomics; Housing; Human; In Situ Hybridization; Informatics; Internet; Java; Laboratories; Lead; Link; Mental disorders; Meta-Analysis; Metadata; Methodology; Methods; Molecular; Mus; Neuroanatomy; Neurons; Neurosciences; Pathway interactions; Pattern; Physiological; Process; Production; Property; Proteins; Publishing; Rattus; Research Personnel; Resource Informatics; Resources; Sampling; Services; Soaps; Source; Staging; Structure; System; Yeasts; base; comparative; data mining; gene interaction; improved; interest; interoperability; open source; programs; protein protein interaction; relating to nervous system; research study; tool; user-friendly; yeast two hybrid system

DESCRIPTION (provided by applicant): This proposal attempts to address the growing need for integrated gene expression informatics resources in neuroscience. The last five years have seen a rapid increase in the production of gene expression in all areas of biology. Analyzing this wealth of data is becoming more and more complex. While there are public data repositories where raw data can be published, there are few if any efforts to provide advanced analytic capabilities that address the specific needs of neuroscience. We propose to create such a facility that will allow neuroscientists to perform sophisticated computational analyses of large quantities of expression data coming from multiple laboratories. Data submitters will be able to control access to their data and the results coming from their data. The project will involve developing a database for meta-analysis of neuroscience-related gene expression data, tools for submission of data, and tools and algorithms for accessing the database and analyzing the data. Users will be able to perform meta-analyses of differential expression, coexpression (correlated expression), differential coexpression, expression detection, and of expression patterns in functionally-related groups of genes. In addition the system will incorporate other genomics data such as sequences, gene pathways and protein-protein interactions. By linking to and overlaying such data, users will be able to better predict the importance of particular analysis results. Finally, we will develop methods to incorporate domain-specific data into gene expression microarray analyses, such as neuroanatomy, neural connectivity and brain in situ hybridizations. This project will enable future collaborative efforts to target specific diseases or processes for examination.

描述（由申请人提供）：该提案试图解决神经科学中对基因表达信息的综合表达信息的需求。 在过去的五年中，生物学所有领域的基因表达产生迅速增加。 分析这些数据丰富的数据变得越来越复杂。 尽管有可以发布原始数据的公共数据存储库，但几乎没有任何努力来提供高级分析能力来满足神经科学的特定需求。 我们建议创建这样的设施，以使神经科学家能够对来自多个实验室的大量表达数据进行复杂的计算分析。 数据提交者将能够控制对其数据的访问以及来自数据的结果。 该项目将涉及开发一个数据库，用于与神经科学相关的基因表达数据，提交数据的工具以及用于访问数据库和分析数据的工具和算法。 用户将能够在功能相关的基因组中执行差分表达，共表达（相关表达），差异共表达，表达检测和表达模式的荟萃分析。 此外，该系统将结合其他基因组学数据，例如序列，基因途径和蛋白质 - 蛋白质相互作用。 通过链接并覆盖此类数据，用户将能够更好地预测特定分析结果的重要性。 最后，我们将开发将域特异性数据纳入基因表达微阵列分析的方法，例如神经解剖学，神经连通性和大脑原位杂交。 该项目将实现未来的合作努力，以针对特定疾病或过程进行检查。