BioinformatJCS Core

生物信息学核心将通过提供定制的实验室与主要用户密切合作 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， 以及一个促进分享实验结果的门户网站。核心会把数据 从一系列质谱平台获得的定性和定量信息 解决我们用户提出的问题。除了便于分析数据外， 使用一系列商业软件的用户，将创建几个新的生物信息学工具， 使当地用户和更广泛的神经科学界受益。我们将继续 开发NeuroPred，这是一种目前可用的基于网络的工具，可以预测激素原 裂解和产生的信号肽。这个预测器提供了一个有价值的联系， 遗传信息编码的蛋白质激素原和肽产品的一个观察。 NeuroProSightPTM是另一个重要的生物信息学工具， 从绝对质量的“自上而下”数据分析中获得完整蛋白质中的修饰。自上而下 这种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、激素和其它神经元特异性蛋白质和肽。最后，A 独特的鸟枪肽组学方法，结合了生物信息学工具和高精度质量 测量将增强肽的表征和鉴定，并将用于 一系列重要的神经科学模型。总之，精心策划的实验，现有的工具， 新的生物信息学能力将创造新的方法和新的数据， 大脑中的信号分子

The Bioinformatics Core will work closely with the major 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. The Core will convert the data acquired from a range of mass spectrometric platforms into qualitative and quantitative information to address the questions posed by our users. Besides facilitating the analysis of the data for the users using a range of commercial software, several new bioinformatics tools will be created to benefit both local users and the broader neuroscience communities. We will continue the development of NeuroPred, a currently available web-based tool that predicts prohormone cleavages and the resulting signaling peptides. This predictor provides a valuable link between genetic information coding for the protein prohormones and the peptide products one observes. NeuroProSightPTM is another important bioinformatics tool that identifies post-translational modifications in intact proteins from "top-down" data 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 neuron-specific proteins and peptides. Lastly, a unique method of shot-gun peptidomics that combines bioinformatics tools and high accuracy mass measurements will enhance peptide characterization and identification, and will be used across a range of important neuroscience models. Together, the well-planned experiments, existing tools, and new bioinformatics capabilities will create novel approaches and new data on the intercellular signaling molecules found in the brain.