Core C - Bioinformatics and Genomics Core

项目摘要 生物信息学和基因组学核心（核心C）将支持项目1 - 3的科学研究 通过协助分析聚糖质谱（MS）和下一代测序（NGS） 数据项目2和3都提出了使用NGS作为研究转录组的工具， 样本之间的差异。NGS实验有能力产生大量的 具有专门数据分析和存储要求的数据。核心C将为所有 本研究计画透过下列特定目标：1：建立一个醣质组学资料库及一个网路 用于存储、处理和分析来自Mass的寡糖数据的应用服务器 光谱实验。这将取代在威奇托州启动的糖组学数据库， 转到堪萨斯大学，发现缺乏基本功能。新数据库 将提供自动数据输入，转换自由文本为基础的MS数据表成一个可搜索的 关系数据库，以及比较糖型制剂聚糖群的更好工具。第二章： 支持分析体外和体内研究产生的基因表达数据 使用微阵列或RNA-seq实验。核心将接收来自项目2和项目3的RNA样本， 监督文库建设和测序，并进行生物信息学数据分析，以确定 差异表达基因3：基因的比较和功能表征 来自体外和体内研究的表达模式。差异表达基因 将进一步分析样本，以将这些基因的功能意义与细胞免疫学中的细胞免疫学功能联系起来。 与卵巢衰老相关的通路和调控网络。

Project Abstract The Bioinformatics and Genomics Core (Core C) will support the scientific investigations of Projects 1-3 by assisting with the analysis of glycan mass spectrometry (MS) and next-generation sequencing (NGS) data. Projects 2 and 3 have both proposed the use of NGS as a tool for investigating the transcriptome- level differences between samples. NGS experiments have the capacity to generate large volumes of data with specialized data analysis and storage requirements. Core C will provide support to all the research projects via the following specific aims: 1: Develop a glycomics database and a web application server for storing, processing and analyzing oligosaccharide data from Mass Spectrometry experiments. This will replace the Glycomics Database initiated at Wichita State, transferred to the University of Kansas, and found to be lacking essential functions. The new database will provide automated data entry, conversion of free-text based MS data tables into a searchable relational database, and better tools for comparing glycan populations of glycoform preparations. 2: Support the analysis of gene expression data generated from both in vitro and in vivo studies using microarray or RNA-seq experiments. The Core will receive RNA samples from Projects 2 and 3, oversee library construction and sequencing and carry out bioinformatics data analyses to identify differentially expressed genes. 3: Comparison and functional characterization of the gene expression patterns from the in vitro and in vivo studies. Differentially expressed genes between samples will be further analyzed to relate the functional significance of these genes with cellular pathways and regulatory networks associated with ovarian senescence.