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的科学调查 通过协助分析葡聚糖质谱(MS)和下一代测序(NGS) 数据。项目2和项目3都建议使用NGS作为研究转录组的工具- 样本之间的级别差异。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。Core C将为所有 通过以下具体目标开展的研究项目：1：开发一个糖类数据库和一个网络 用于存储、处理和分析来自海量的寡糖数据的应用服务器 光谱实验。这将取代威奇托州启动的Glycomics数据库， 转到堪萨斯大学，发现缺乏必要的功能。新的数据库 将提供自动数据输入，将基于自由文本的MS数据表转换为可搜索的 关系数据库，和更好的工具来比较糖形制剂的糖链种群。2： 支持对来自体外和体内研究的基因表达数据进行分析 使用微阵列或RNA-SEQ实验。核心将从项目2和项目3接收RNA样本， 监督文库建设和测序，并进行生物信息学数据分析，以识别 差异表达的基因。3：基因的比对和功能鉴定 来自体外和体内研究的表达模式。差异表达的基因在 将对样本进行进一步分析，以将这些基因的功能意义与细胞 与卵巢衰老相关的途径和调控网络。

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.