BIOINFORMATICS CORE

生物信息学核心

• 批准号: 7640650
• 负责人: SANDRA L RODRIGUEZ ZAS
• 金额: $ 36.25万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7640650
• 关键词: Address; Amino Acid Sequence; Animal Model; Bioinformatics; Biological; Boxing; Brain; Code; Communities; Computer software; Custom; Data; Data Set; Databases; Development; Gene Expression Profile; Generations; Genetic; Grant; Hormones; Internet; Laboratories; Link; Nature; Neurons; Neuropeptides; Online Systems; Peptide Sequence Determination; Peptides; Process; Proteins; Proteome; Proteomics; Range; Readability; Research Personnel; Sampling; Signal Transduction; Signaling Protein; System; Training; United States National Institutes of Health; Work; Writing; base; cytokine; data management; novel strategies; prohormone; research study; tool

The proposed Bioinformatics Core will work closely with the biological users by providing a customized laboratory sample tracking system, an efficient and quick data pipeline, a tailored project management system, and a web portal to facilitate sharing of experimental results. In addition, the worldwide scientific community will be able to search and download from the completed database through this web portal. A top priority and a major benefit to the users will be custom written analysis software to address the specific needs of the investigators. One project is the development of an intercellular protein / peptide predictor that predicts prohormone cleavage; this facilitates the accurate prediction of the final enzymatic products. This predictor will provide a valuable link between genetic information coding for the long protein prohormones and the products one observes. NeuroProSightPTM will be developed, which is a bioinformatics tool that identifies PTMs in intact proteins through a "top-down" analysis of absolute masses. The top-down approach will enable investigators to use absolute masses of intact proteins to identify neuropeptides, cytokines, hormones, and other intercellular signaling. In addition, bioinformatics tools will be written to comprehensively compare data from both microarrays and proteomics experimentation using a range of animal models to gain a better understanding of relationships between the transcriptome and proteome. Together these exciting bioinformatics advances will create new tools to provide new approaches to study intercellular signaling proteins of the brain - essentially theorizing and experimenting "out of the box".

拟议的生物信息学核心将与生物用户密切合作， 定制的实验室样品跟踪系统，高效快速的数据管道，量身定制的 项目管理系统，以及一个门户网站，以促进分享实验结果。在 此外，全球科学界将能够从 通过这个门户网站完成数据库。用户的一个最优先事项和一个主要好处将是定制书面分析软件，以满足调查人员的具体需求。一个项目是开发一种细胞间蛋白质/肽预测因子，预测激素原裂解;这有助于准确预测最终的酶促产物。这个预测器将提供一个有价值的链接之间的遗传信息编码的长蛋白质激素原和产品的观察。将开发NeuroProSightPTM，这是一种生物信息学工具，通过对绝对质量的“自上而下”分析来识别完整蛋白质中的PTM。自上而下的方法将使研究人员能够使用完整蛋白质的绝对质量来识别神经肽，细胞因子，激素和其他细胞间信号。此外，将编写生物信息学工具，使用一系列动物模型全面比较来自微阵列和蛋白质组学实验的数据，以更好地了解转录组和蛋白质组之间的关系。这些令人兴奋的生物信息学进展将创造新的工具，为研究大脑细胞间信号蛋白提供新的方法-基本上是理论化和实验“开箱即用”。