Bioinformatics and Modeling Core

生物信息学和建模核心

• 批准号: 10704365
• 负责人: Matthew Tyson Weirauch
• 金额: $ 16.05万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10704365
• 关键词: ATAC-seq; Address; Affect; Allergic Disease; American; Autoimmune; Binding; Bioinformatics; Biological Assay; Biomedical Research; Blood; Cells; ChIP-seq; Chromatin; Chromatin Loop; Code; Collaborations; Communities; Complex; Computational Technique; Computer software; Consult; DNA; Data; Data Analyses; Data Analytics; Data Collection; Data Set; Data Storage and Retrieval; Databases; Deposition; Disease; Emerging Technologies; Epigenetic Process; Experimental Designs; Flow Cytometry; Functional disorder; Gene Expression; Gene Expression Regulation; Genetic; Genomics; Genotype; Goals; Immunologist; Immunophenotyping; Inflammatory; Informatics; Institution; Knowledge; Longitudinal Studies; Measures; Medical; Medical center; Metadata; Methodology; Methods; Modeling; Modernization; Molecular; Molecular Disease; Nucleic Acid Binding; Pediatric Hospitals; Phenotype; Prevention strategy; Process; Proteins; Proteomics; Publishing; Quality Control; RNA; RNA Sequences; RNA-Binding Proteins; Records; Reproducibility; Research; Research Personnel; Research Support; Resources; Rheumatism; Sampling; Services; System; Therapeutic; Tissue Banks; Tissue Sample; Tissue-Specific Gene Expression; United States National Institutes of Health; Universities; analysis pipeline; base; bioinformatics pipeline; computerized tools; crosslinking and immunoprecipitation sequencing; data centers; data integration; data management; data repository; deep learning; design; diagnostic strategy; experience; experimental study; functional genomics; genetic variant; genome sequencing; genomic data; high dimensionality; innovation; insight; large datasets; member; metadata standards; multidimensional data; novel; polygenic risk score; public database; single-cell RNA sequencing; tool; transcription factor; transcriptome sequencing; transcriptomics; variant of interest; virtual; whole genome; wiki

Project Summary/Abstract – Bioinformatics and Modeling (BAM) Core Rheumatic diseases adversely affect the lives of millions of Americans. Yet, modern therapies remain largely ineffective. Detailed knowledge of molecular disease mechanisms transforms medical management, therapeutic approaches, diagnostics, and preventive strategies. Advances in bioinformatic and modeling approaches have been, and will continue to be, tantamount to revealing rheumatic disease mechanisms. The goal of the Bioinformatics and Modeling (BAM) Core is to drive the quality control, analysis, integration, modeling, and dissemination of large datasets to understand inflammatory and rheumatic diseases. To this end, the BAM Core will continue to offer unique computational services and expertise to the P30 research community, the Cincinnati Children’s Hospital Medical Center and University of Cincinnati research community, and collaborators at other institutions. The BAM Core will implement innovative genomics and immunophenotyping data management and analytic strategies to interrogate the datasets generated by users of the Cincinnati Rheumatic Disease Resource Center. Publicly available software packages and newly developed, innovative tools will be integrated, automated, applied and made available to the larger research community. The following Specific Aims will be spearheaded by The BAM Core in close collaboration with the Research Base investigators and the Functional Genomics, Integrative Cell Phenotyping, and Tissue Repository Cores: Aim 1. To provide analytic expertise and informatic support for functional genomic experiments. Aim 2. To support genotype-dependent analysis of functional genomic experiments. Aim 3. To analyze high-dimensional flow cytometry data. Aim 4. To facilitate the organization and deposition of genetic, genomic, and proteomic data.

项目摘要/摘要-生物信息学和建模（BAM）核心