Bioinformatics/Biostatistics Core

CONTE生物信息学和生物统计核心具有与CONTE研究人员密切互动的强大历史，包括目前的中心赠款资助期，联合出版物和联合开发新的计算算法和用户友好的软件应用程序证明了这一点。核心中心将继续支持所支持的项目和试点活动对生物信息学和生物统计学日益增长的需求。正如这些项目中提出的，对5-羟色胺信号在整个生命周期中的表观基因组、转录和蛋白质组变化进行全球表征，最终将有助于阐明导致多种大脑疾病的复杂分子机制。然而，我们在处理、分析、集成和解释由多层次、数据丰富的方法生成的大数据集方面面临着巨大的挑战。核心的一个主要目标是提供计算支持，以加速跨多维数据集的科学发现。我们通过为数据存储、数据共享和数据挖掘提供支持来实现这一目标。我们利用一个正式的数据分类方案，该方案具有四个数据级别，便于定位和交换感兴趣的数据。我们为实验设计和统计数据分析提供支持，确保实验得到良好的计划和动力，并以良好的统计设计标准进行。我们使用稳健的现代统计模型以及探索性的图形技术进行数据分析。该核心为基于路径和网络的数据集成和分析提供支持，这对于拟议的基因组和转录组范围内对发育中的5-羟色胺信号诱导的变化的表征至关重要。核心在促进整合各个项目产生的数据集方面发挥了关键作用，通过路径和基于网络的数据分析可以最好地实现这一点，并利用路径一级的统计分析和可视化。

The Conte Bioinformatics and Biostatistics Core has a strong history of close interaction with Conte investigators including the current Center grant funding period, as evidenced by joint publications and the joint development of novel computational algorithms and user-friendly software applications. The Core will continue to sustain the increasing bioinformatics and biostatistics needs of the supported projects and pilot activities. As proposed in the projects, global characterization of epigenomic, transcriptomic, and proteomic changes in response to 5-HT signaling across the life-span will eventually help elucidate the complex molecular mechanisms underlying multiple brain disorders. However, we face tremendous challenges in processing, analyzing, integrating, and interpreting large and heterogeneous datasets generated by multi-level, data rich approaches. A major goal of the Core is to provide computational support to expedite scientific discoveries across multidimensional data sets. We achieve the goal by providing support for data storage, data sharing, and data mining. We utilize a formal data categorization scheme with four data levels that facilitate the location and exchange of data of interest. We provide support for experimental design and statistical data analysis, ensuring that experiments are well planned and powered and pursued with the standards of good statistical design. We perform data analysis using robust, modern statistical models as well as with exploratory graphical techniques. The Core provides support for pathway and network-based data integration and analysis that will be critical for the proposed genome- and transcriptome-wide characterizations of changes induced by developmental 5-HT signaling. The Core plays a critical role in facilitating the integration of data sets generated by individual projects, which can be best achieved through pathway and network-based data analysis and takes advantage of pathway-level statistical analysis and visualization.