Data Analysis

数据分析

• 批准号: 8932067
• 负责人: Jacob David Jaffe
• 金额: $ 34.11万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8932067
• 关键词: Algorithms; Automatic Data Processing; Back; Bioinformatics; Biological Assay; Biological Models; Cancer Etiology; Cell model; Cells; Chromatin; Communities; Data; Data Analyses; Data Collection; Databases; Disease; Drug Targeting; Epigenetic Process; Etiology; Event; Future; Gene Silencing; Goals; Instruction; Learning; Libraries; Mass Spectrum Analysis; Mediating; Molecular; Network-based; Neurons; Online Systems; Phosphorylation; Proteomics; Psychological reinforcement; Quality Control; Reading; Research; Research Infrastructure; Resources; Signal Transduction; System; Techniques; Technology; Testing; base; chromatin modification; data management; developmental genetics; human embryonic stem cell; insight; member; next generation; novel therapeutics; programs; research study; response; small molecule; tool

The overarching goal of this project is to test the hypothesis that modulation of phosphorylation-mediated signaling events in response to perturbations can establish new cellular states by altering their epigenetic landscapes. To achieve this goal, we propose performing mass spectrometry (MS)-based proteomic assays that specifically target quantitative readouts of phosphosignaling and chromatin modifications in cells on > 15,000 perturbational conditions. These perturbations will focus on modulation of signaling cascades and epigenetic marks by small molecules and gene inactivations. We will study several different cellular model systems, including comprehensive studies neuronal lineage differentiation starting from human embryonic stem cells. We propose to establish a center.in order to develop the necessary infrastructure, pipelines, data management, and analytics required to perform what would be the largest set of related experiments with MS proteomic read outs to date. We will also explore next-generation MS acquisition technologies to establish a permanently minable MS data resource that will be accessible to the public. We will contribute the resulting data and tools to the Library of Integrated Network-based Cellular Signatures (LINCS) program for the purpose of making connections among disparate perturbations through phosphoproteomic and chromatin modification signatures in concert with other data types to be contributed to LINCS by other centers. The resulting analyses will help identify novel therapeutic opportunities and synergies, as dysregulation of phosphosignaling and epigenetic systems are two of the most common molecular etiologies identified in a growing number of genetic, developmental, and environmental diseases. In this component of the project we describe the data analysis pipelines, advanced statistical and bioinformatic techniques, and data repository strategies that we will use to prosecute the project. We also discuss how end-users outside of our center will access, analyze, visualize, and interact with the data that we generate through web-based tools that we will develop.

这个项目的首要目标是检验这样一种假设，即磷酸化调节介导的 响应扰动的信号事件可以通过改变表观遗传来建立新的细胞状态 风景画。为了实现这一目标，我们建议进行基于质谱学(MS)的蛋白质组分析 特异性靶向于细胞中磷信号和染色质修饰的定量读数； 15,000个微扰条件。这些扰动将集中在信令级联的调制和 小分子和基因失活的表观遗传标记。我们将研究几种不同的细胞模型 系统，包括从人类胚胎开始的神经元谱系分化的全面研究 干细胞。我们建议建立一个中心，以发展必要的基础设施、管道、数据 执行最大规模的相关实验所需的管理和分析 到目前为止，MS蛋白质组读出了。我们还将探索下一代MS获取技术，以 建立公众可访问的永久可开采的MS数据资源。我们将做出贡献 将产生的数据和工具发送到基于网络的综合蜂窝签名库(LINCS)计划 为了在不同的扰动之间建立联系，通过磷酸蛋白质组和 染色质修改签名与其他数据类型一起由其他人提供给LINCS 中锋。由此产生的分析将有助于确定新的治疗机会和协同效应，因为 磷信号和表观遗传系统的失调是两种最常见的分子病因 在越来越多的遗传、发育和环境疾病中被发现。 在该项目的此组件中，我们描述了数据分析管道、高级统计和 生物信息学技术，以及我们将用来进行该项目的数据存储库策略。我们也 讨论我们中心以外的终端用户将如何访问、分析、可视化数据并与之交互 我们通过我们将开发的基于网络的工具来生成。