Bioinformatics for Protein Microarrays

蛋白质微阵列生物信息学

• 批准号: 7564732
• 负责人: RICHARD C ZANGAR
• 金额: $ 32.15万
• 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 2011-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7564732
• 关键词: Accounting; Adopted; Advanced Development; Age; Algorithms; Antibodies; Area; Bioinformatics; Biological Assay; Biological Markers; Biomedical Computing; Biomedical Research; Classification; Clinical; Collaborations; Complex; Computational Science; Computer software; 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 Sciences; Institutes; Laboratories; Laboratory Procedures; Link; Metadata; Micro Array Data; Microarray Analysis; Modeling; Monitor; NIH Program Announcements; Principal Investigator; Printing; Procedures; Process; Process Assessment; Protein Microchips; Proteins; Proteomics; Protocols documentation; Quality Control; Race; Relative (related person); Reproducibility; Research; Research Personnel; Sampling; Signal Transduction; Software Tools; Source; Staging; Statistical Methods; Study Section; System; 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; protein profiling; 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（由申请人提供）：抗体微阵列是一种新兴技术，具有有效和定量分析数千个样品中许多蛋白质的潜力。因此，该技术可以提供用于确定潜在生物标志物的个体或谱的临床有用性的迫切需要的机制。然而，目前，抗体微阵列分析缺乏指导原则、标准程序、磨练的实验室实践、基础统计和支持软件来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方案和支持软件（“ProMAT”）。该提案的目标是将抗体微阵列推进到可以用作临床生物标志物验证的常规工具的程度。为了实现这一目标，我们计划建立新的协议，使用内部和外部标准，开发统计基础，以评估数据收集和分析的所有阶段的数据质量，并开发一个复杂的生物信息学工具，用于快速数据分析，包括先进的质量控制功能。这一系统还将有助于查明数据可变性的来源，并使数据正常化。我们将使用一个迭代过程，通过解决测定要求，推导统计方法和组成原型软件，磨练实验室实践和测定程序，并通过重复实验评估进展，重点是评估数据质量和再现性。在这项工作完成后，我们将揭示进行抗体微阵列实验的指导原则和要求，并开发一个集成系统，用于快速生成评估生物标志物谱的临床潜力所需的高质量数据。

项目成果

High-throughput analysis of serum antigens using sandwich ELISAs on microarrays.

• DOI: 10.1007/978-1-60327-811-9_10
• 发表时间: 2009
• 期刊: Methods in molecular biology
• 作者: S. Servoss;Rachel M. Gonzalez;S. Varnum;R. Zangar

Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation.

使用 ELISA 微阵列测定、单调样条和蒙特卡罗模拟预测蛋白质浓度。

• DOI: 10.2202/1544-6115.1364
• 发表时间: 2008
• 期刊: Statistical applications in genetics and molecular biology
• 影响因子: 0.9
• 作者: Daly,DonSimone;Anderson,KevinK;White,AmandaM;Gonzalez,RachelM;Varnum,SusanM;Zangar,RichardC
• 通讯作者: Zangar,RichardC

Reactive oxygen species alter autocrine and paracrine signaling.

活性氧会改变自分泌和旁分泌信号。

• DOI: 10.1016/j.freeradbiomed.2011.09.001
• 发表时间: 2011
• 期刊: Free radical biology & medicine
• 影响因子: 7.4
• 作者: Zangar,RichardC;Bollinger,Nikki;Weber,ThomasJ;Tan,RuiminM;Markillie,LMeng;Karin,NormanJ
• 通讯作者: Karin,NormanJ

Antibody microarrays for high-throughput, multianalyte analysis.

用于高通量多分析物分析的抗体微阵列。

• DOI: 10.3233/cbm-2009-0140
• 发表时间: 2010
• 期刊: Cancer biomarkers : section A of Disease markers
• 作者: Jin,Hongjun;Zangar,RichardC
• 通讯作者: Zangar,RichardC

ELISA-BASE: an integrated bioinformatics tool for analyzing and tracking ELISA microarray data.

ELISA-BASE：一种用于分析和跟踪 ELISA 微阵列数据的集成生物信息学工具。

• DOI: 10.1093/bioinformatics/btp182
• 发表时间: 2009
• 期刊: Bioinformatics (Oxford, England)
• 作者: White,AmandaM;Collett,JamesR;Seurynck-Servoss,ShannonL;Daly,DonS;Zangar,RichardC
• 通讯作者: Zangar,RichardC