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通过提供一个与生物使用者紧密合作 定制的实验室样品跟踪系统，高效且快速的数据管道，量身定制 项目管理系统和网站门户，可促进共享实验结果。在 此外，全球科学界将能够从 通过此Web门户完成数据库。用户的重中之重和重大好处将是定制的书面分析软件，以满足调查人员的特定需求。一个项目是开发细胞间蛋白 /肽预测因子，该预测能够预测性激素裂解。这促进了最终酶促产品的准确预测。该预测因子将在长蛋白激素的遗传信息编码与人们观察到的产物之间提供有价值的联系。将开发NeuroProsightPTM，这是一种生物信息学工具，可以通过对绝对质量的“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鉴定神经肽，细胞因子，激素和其他细胞间信号传导。此外，使用一系列动物模型来全面比较微阵列和蛋白质组学实验的数据，以便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步将共同创建新的工具，以提供新的方法来研究大脑的细胞间信号传导蛋白 - 本质上是理论化和实验“开箱即用”。