Bioinformatics Core

生物信息学核心

• 批准号: 10404438
• 负责人: Matteo Pellegrini
• 金额: $ 39.22万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10404438
• 关键词: Acne; Bioinformatics; Biology; Biopsy; Cells; Complex Mixtures; Data; Data Analyses; Data Set; Disease; Disease model; Familiarity; Generations; Genes; Genetic; Genomics; Human; Immune; Immune response; Individual; Inflammatory; Lead; Measures; Methodology; Modality; Modeling; Process; Research; Research Personnel; Sampling; Services; Skin; Techniques; Technology; cell type; data analysis pipeline; data integration; data tools; data visualization; disorder control; experience; genomic data; innovation; lipid metabolism; lipidome; lipidomics; member; microbiome; multiple data types; novel therapeutics; programs; repository; single cell analysis; tool; transcriptome; transcriptome sequencing; transcriptomics; two-dimensional; web site

PROJECT SUMMARY/ABSTRACT Bioinformatics Core The purpose of this Core is to provide bioinformatic analysis of transcriptomic data. Our Core will provide the essential data analysis service to render this data accessible and interpretable to the members of this consortium. The directors and staff of this Core have extensive experience in the analysis of genomic data, as well as familiarity with the underlying biology of the associated projects. Specifically, we will process bulk, single cell and spatial transcriptomic data using existing pipelines. Moreover, we have developed tools to interpret transcriptomic profiles in terms of cell type and inflammatory signatures. We also have expertise in the use of data integration tools to combine our transcriptomic data with genetic and lipidomic data. Finally, we will provide tools for data visualization, such as an R Shiny server for viewing individual genes in two dimensional projections of single cell transcriptomes. The Core we are proposing here will allow all the groups within this CORT to receive analyzed data that can be directly interpreted by researchers without extensive computational expertise. This functionality should render genomics research far more accessible to all members of this CORT.

项目总结/文摘