Bioinformatics and Computational Biology Core

生物信息学和计算生物学核心

• 批准号: 10453789
• 负责人: Wei Wang
• 金额: $ 17.24万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-17 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10453789
• 关键词: ATAC-seq; Acute; Binding Sites; Bioinformatics; Biological; Biology; CD8-Positive T-Lymphocytes; CD8B1 gene; Cells; Cellular biology; ChIP-seq; Chronic; Collaborations; Common Core; Computational Biology; Computer Analysis; Computing Methodologies; Data; Data Analyses; Data Set; Databases; Deposition; Development; Enhancers; Ensure; Epigenetic Process; Experimental Designs; Generations; Genetic; Genetic Transcription; Glean; Goals; Growth; Immune response; Individual; Laboratories; Link; Memory; Methodology; Methods; Mission; Molecular; Mus; Pathway Analysis; Pathway interactions; Process; Quality Control; Research; Research Personnel; Research Project Grants; Sampling; Supervision; System; T memory cell; T-Lymphocyte; T-Lymphocyte Subsets; Techniques; Tissues; United States National Institutes of Health; Virus Diseases; Work; acute infection; base; bioinformatics pipeline; bioinformatics tool; chronic infection; computational platform; computerized data processing; data sharing; data submission; denoising; epigenomics; exhaustion; experience; experimental study; histone modification; innovation; insight; large datasets; mouse development; multidimensional data; novel; programs; response; single cell analysis; single-cell RNA sequencing; synergism; transcription factor; transcriptome sequencing; transcriptomics; web interface; ATAC-seq; Acute; Binding Sites; Bioinformatics; Biological; Biology; CD8-Positive T-Lymphocytes; CD8B1 gene; Cells; Cellular biology; ChIP-seq; Chronic; Collaborations; Common Core; Computational Biology; Computer Analysis; Computing Methodologies; Data; Data Analyses; Data Set; Databases; Deposition; Development; Enhancers; Ensure; Epigenetic Process; Experimental Designs; Generations; Genetic; Genetic Transcription; Glean; Goals; Growth; Immune response; Individual; Laboratories; Link; Memory; Methodology; Methods; Mission; Molecular; Mus; Pathway Analysis; Pathway interactions; Process; Quality Control; Research; Research Personnel; Research Project Grants; Sampling; Supervision; System; T memory cell; T-Lymphocyte; T-Lymphocyte Subsets; Techniques; Tissues; United States National Institutes of Health; Virus Diseases; Work; acute infection; base; bioinformatics pipeline; bioinformatics tool; chronic infection; computational platform; computerized data processing; data sharing; data submission; denoising; epigenomics; exhaustion; experience; experimental study; histone modification; innovation; insight; large datasets; mouse development; multidimensional data; novel; programs; response; single cell analysis; single-cell RNA sequencing; synergism; transcription factor; transcriptome sequencing; transcriptomics; web interface

SUMMARY-BIOINFORMATICS AND COMPUTATIONAL BIOLOGY CORE: The Bioinformatics and Computational Biology Core will support all three Projects and the Single-Cell Transcriptomics and Epigenetics Core (SCTE) in a range of activities related to data processing, storage, distribution and integrative analysis. A key role of the Core is to provide a centralized portal for integrative analysis of the different omics data (RNA-seq, ChIP-seq and ATAC-seq) to be generated by the Projects and SCTE Core. The goal is to illuminate the transcriptomic and epigenomic landscape of T cells in response to acute and chronic viral infection, and uncover the critical regulators that determine the state or fate of T cells. The Core will utilize advanced bioinformatics tools for the high-dimensional data matrices generated at different stages of the immune response and in distinct tissues by the Program Project and will apply innovative techniques to discover core regulators. The Core will assist the three Projects and SCTE Core for experimental design, and work closely with the other Investigators to analyze individual data sets and also the combined data set. In particular, the Core will establish a data deposit, tracking, storage and distribution system to allow data sharing and sample tracking among all the participating laboratories. The Core will also establish three bioinformatics pipelines to process RNA-seq, ChIP-seq and ATAC-seq data respectively, including sequencing read mapping, quality control and peak calling. Advanced analyses such as enhancer prediction, motif analysis and genetic network analysis will also be conducted to reveal the key regulators critical for defining particular T cell states.

摘要生物信息学和计算生物学核心： 生物信息学和计算生物学核心将支持所有三个项目和单细胞 转录组学和表观遗传学核心（SCTE）在与数据处理，存储相关的一系列活动中 分布和综合分析。核心的关键作用是为综合提供集中门户 分析项目要生成的不同的OMIC数据（RNA-Seq，ChIP-Seq和ATAC-Seq） 和SCTE核心。目的是阐明T细胞中T细胞的转录组和表观基因组景观 对急性和慢性病毒感染的反应，并发现确定状态或 T细胞的命运。核心将利用高维数据矩阵的高级生物信息学工具 通过程序项目在免疫反应的不同阶段和不同组织中产生 将采用创新技术来发现核心调节器。核心将协助这三个项目，并 实验设计的SCTE核心，并与其他研究人员紧密合作以分析单个数据 集合以及组合数据集。特别是，核心将建立数据存款，跟踪，存储 和分配系统，以允许所有参与实验室之间的数据共享和样本跟踪。 核心还将建立三个生物信息学管道来处理RNA-Seq，Chip-Seq和ATAC-Seq 数据分别包括测序读取映射，质量控制和峰值调用。高级分析 例如增强子预测，基序分析和遗传网络分析也将进行揭示 关键调节剂对于定义特定T细胞状态至关重要。