Bioinformatics Core

生物信息学核心--摘要 在我们最初的资助期间，NV INBRE生物信息学核心支持研究调查细胞 通过提供完善的实验设计和基础生物医学的统计分析来实现成长和分化 和临床实验；下一代全基因组和全转录组测序分析 数据、蛋白质组数据、微阵列数据；计算资源和基础设施。核心将继续 提供支持实验设计、基础科学和统计分析的资源和服务 临床研究，蛋白质组数据分析，途径分析，全基因组关联研究，以及 下一代测序数据的生成和分析。在此次续订中，核心将增长以支持 设计和分析更先进的临床研究，包括一项支持更复杂的新倡议 基于全基因组测序和SNP芯片技术的疾病相关性研究。此外， CORE将在全州范围内开发和实施强大和多样化的生物信息学外联和培训 在我们的外展机构教授、培训和指导本科生的计划，以纳入Big 数据转化为生物医学研究。该计划将包括1)生物信息学研究体验 在外展机构为本科生提供现场培训课程，提供动手、一对一 辅导和培训与其生物信息学课堂主题相关的工具和方法的使用或 研究，2)生物信息学研讨会，重点是分析基因组、环境、医学、 经济、社交网络数据以及检查这些数据的工具，以及3)大数据分析培训模块 在该课程中，学生将学习从复杂数据库中组合大数据集的基本方法。

Bioinformatics Core - Abstract During our initial funding periods, the NV INBRE Bioinformatics Core supported research investigating Cell Growth and Differentiation by providing sound experimental design and statistical analysis of basic biomedical and clinical experiments; analysis of whole-genome and whole-transcriptome next-generation sequencing data, proteomic data, microarray data; computational resources and infrastructure. The Core will continue to provide resources and services supporting experimental design, statistical analysis of basic science and clinical studies, analysis of proteomic data, pathway analysis, genome-wide association studies, and generation and analysis of next-generation sequencing data. In this renewal, the Core will grow to support the design and analysis of more advanced clinical studies, including a new initiative to support more sophisticated disease association studies based on whole-genome sequencing and SNP chip technology. In addition, The Core will develop and implement a strong and diverse statewide Bioinformatics Outreach and Training Program to teach, train, and mentor undergraduate students in our Outreach Institutions to incorporate Big Data into biomedical research. This program will include 1) Bioinformatics Research Experiences offering on-site training sessions for undergraduates at the Outreach Institutions to provide hands-on, one-on-one tutoring and training in the use of tools and approaches relevant to their bioinformatics classroom topics or research, 2) Bioinformatics Workshops focusing on tools to analyze genomic, environmental, medical, economic, and social network data, and tools to examine them, and 3) Big Data Analytics Training Modules in which students will learn basic approaches to combining large datasets from complex databases.