Transcriptome & Networks Analysis Core

转录组

• 批准号: 10593070
• 负责人: Jose Luis Gonzalez Hernandez
• 金额: $ 38.92万
• 依托单位: SOUTH DAKOTA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-20 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10593070
• 关键词: Access to Information; Acute-Phase Reaction; Adoption; Algorithms; Antibodies; Bar Codes; Binding; Biochemical; Bioinformatics; Biomedical Research; Cell Death; Cells; Cilia; Clustered Regularly Interspaced Short Palindromic Repeats; Cryoultramicrotomy; Data; Data Analyses; Data Set; Experimental Designs; Face; Frequencies; Funding; Future; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Transcription; Genomics; Goals; Individual; Inflammation; Inflammation Process; Inflammatory; Libraries; Lymphangiogenesis; Lymphatic; Macrophage; Measurement; Mediating; Meta-Analysis; Methods; Microscopy; Molecular; Pathway Analysis; Pathway interactions; Pattern; Phenotype; Preparation; Printing; Proteomics; Public Domains; Research Personnel; Research Project Grants; Resolution; Series; Site; Small RNA; Surveys; TNF gene; Techniques; Technology; Testing; Time; Tissue-Specific Gene Expression; Tissues; Translating; Translational Research; United States National Institutes of Health; Validation; Work; bioinformatics resource; bioinformatics tool; cell type; data integration; deep sequencing; differential expression; experience; experimental analysis; gene function; gene network; gene regulatory network; genome-wide; genome-wide analysis; innovation; insight; interactive tool; interdisciplinary collaboration; large datasets; new technology; next generation sequencing; novel; optical imaging; programs; response; screening; single-cell RNA sequencing; skills; tissue repair; tool; transcription factor; transcriptome; transcriptome sequencing; transcriptomics; whole genome; wound

Project Summary – Core B: TRANSCRIPTOME AND NETWORK ANALYSIS CORE The advent of high-throughput omics technologies enables powerful analyses of cellular transcriptional programs, gene-function relationships and genome-wide surveys at unprecedented detail. Individual investigators face many hurdles in implementing these new technologies and effectively translating these large datasets into mechanistic understanding of molecular pathways. The goal of the Transcriptome and Network Analysis Core (TNAC) is to facilitate the effective use of omics technologists and the downstream bioinformatics analyses. This core leverages the expertise of Dr. Gonzalez Hernandez, Director of the SDSU Genomics Sequencing Facility, with expertise in genetics and genomics analysis, and Dr. Xijin Ge, experienced bioinformatician and biomedical researcher. Specifically, this core will enable the project leads to use the following technology to study inflammation: RNA sequencing (RNA-seq), CRISPR whole genome screening, spatially resolved RNA-seq, and proteomics. The TNAC has 3 specific aims: 1) Transcriptomic analyses by conventional RNA-Seq and deep sequencing for analysis of CRISPR insertions; 2) The use of spatially resolved and single cell RNA-seq technology and associated bioinformatics workflows; and 3) Data integration and extensive pathway analysis using and adapting bioinformatics tools and resources, including those developed by Dr. Xijin Ge, to construct gene regulatory networks underlying inflammation, integrate proteomics data, and conduct meta-analysis of data generated by the three projects alongside data in the public domain. This core is innovative in that it brings together cutting-edge experimental technology with the latest bioinformatics tools and approaches. Working closely with the four project leads, this core will exemplify interdisciplinary collaboration, and significantly promote the adoption of cutting-edge technologies among biomedical researchers in the region.

项目总结-核心B：转录组和网络分析核心