Bioinformatics for Protein Microarrays

蛋白质微阵列生物信息学

• 批准号: 7194452
• 负责人: RICHARD C ZANGAR
• 金额: $ 31.65万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-02-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7194452
• 关键词: Accounting; Adopted; Advanced Development; Age; Algorithms; Antibodies; Area; Bioinformatics; Biological Assay; Biological Markers; Biological Process; Biomedical Computing; Biomedical Research; Classification; Clinical; Collaborations; Complex; Computational Science; Computer software; Condition; Data; Data Analyses; Data Collection; Data Quality; Data Sources; Data Storage and Retrieval; Databases; Development; Diagnostic; Disease; Drug effect disorder; Electronics; Emerging Technologies; Environment; Enzyme-Linked Immunosorbent Assay; Foundations; Funding; Gender; Goals; Grant; Human; Image; Image Analysis; Imagery; Individual; Information Retrieval; Information Sciences; Institutes; Laboratories; Laboratory Procedures; Link; Metadata; Micro Array Data; Microarray Analysis; Modeling; Monitor; NIH Program Announcements; Numbers; Principal Investigator; Printing; Procedures; Process; Process Assessment; Protein Microchips; Proteins; Proteomics; Protocols documentation; Purpose; Quality Control; Race; Rate; Relative (related person); Reproducibility; Research; Research Personnel; Sampling; Signal Transduction; Software Tools; Source; Staging; Standards of Weights and Measures; Statistical Methods; Study Section; System; Systems Analysis; Technology; Testing; Time; United States National Institutes of Health; Validation; Variant; Work; analytical tool; clinically relevant; computerized data processing; data integration; design; experience; graphical user interface; interest; models and simulation; novel; open source; platform-independent; programs; prototype; research and development; research study; response; software development; sound; statistics; tool; tool development

DESCRIPTION (provided by applicant): Antibody micro arrays are an emerging technology that has the potential to efficiently and quantitatively analyze many proteins in thousands of samples. Therefore, this technology can provide a badly needed mechanism for determining the clinical usefulness of individual or profiles of potential biomarkers. At present, though, antibody micro array analysis lacks the guiding principles, standard procedures, honed laboratory practices, foundational statistics and supporting software to produce quality results on a large scale. Therefore, we have started to develop both the protocols and supporting software ("ProMAT") specifically for analyzing protein micro array data. The goal of this proposal is to advance antibody micro array to the point that it can be used as a routine tool for clinical biomarker validation. To accomplish this goal, we plan to establish novel protocols for the use of internal and external standards, develop the statistical foundation for evaluating data quality at all stages of data collection and analysis, and develop a sophisticated bioinformatics tool for rapid data analysis, including advanced quality control features. This system will also aid in identifying sources of data variability and will allow for data normalization. We will use an iterative process that cycles through resolving assay requirements, deriving statistical methods and composing prototype software, honing laboratory practices and assay procedures, and evaluating progress through repetitive experimentation that focuses on assessing data quality and reproducibility. At the completion of this work, we will have uncovered guiding principles and requirements for conducting antibody micro array experiments and developed an integrated system for rapidly generating the high quality data required to evaluate the clinical potential of biomarker profiles.

描述(申请人提供)：抗体微阵列是一项新兴的技术，具有有效和定量分析数千个样本中的许多蛋白质的潜力。因此，这项技术可以提供一种迫切需要的机制来确定单个或潜在生物标记物的临床实用性。然而，目前，抗体微阵列分析缺乏指导原则、标准程序、经过磨练的实验室实践、基础统计和支持软件，无法大规模产生高质量的结果。因此，我们已经开始开发专门用于分析蛋白质微阵列数据的协议和支持软件(“Promat”)。这项建议的目的是将抗体微阵列推进到可以作为临床生物标记物验证的常规工具的程度。为了实现这一目标，我们计划为使用内部和外部标准建立新的协议，为评估数据收集和分析的所有阶段的数据质量建立统计学基础，并开发一种先进的生物信息学工具，用于快速数据分析，包括先进的质量控制功能。该系统还将帮助查明数据可变性的来源，并使数据标准化。我们将使用迭代过程，通过解决分析要求、推导统计方法和组成原型软件、磨练实验室实践和分析程序，以及通过侧重于评估数据质量和重复性的重复实验来评估进展。在这项工作完成后，我们将发现进行抗体微阵列实验的指导原则和要求，并开发了一个集成系统，用于快速生成评估生物标记物图谱临床潜力所需的高质量数据。