Bioinformatics/Biostatistics Core

康特生物信息学和生物统计学核心与康特研究人员有着密切互动的悠久历史，包括目前的中心赠款资助期，这一点可以通过联合出版物和联合开发新型计算算法和用户友好的软件应用程序来证明。核心方案将继续满足受支助项目和试点活动日益增加的生物信息学和生物统计学需求。正如项目中所提出的，对整个生命周期中响应5-HT信号传导的表观基因组、转录组和蛋白质组变化的全球表征最终将有助于阐明多种脑疾病背后的复杂分子机制。然而，我们面临着巨大的挑战，在处理，分析，集成和解释大型和异构数据集产生的多层次，数据丰富的方法。核心的一个主要目标是提供计算支持，以加快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，四个数据级别，方便感兴趣的数据的位置和交换。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规划和支持，并符合良好统计设计的标准。我们使用强大的现代统计模型以及探索性图形技术进行数据分析。该核心为基于途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发育5-HT信号传导诱导的变化特征至关重要。核心在促进整合各个项目产生的数据集方面发挥着关键作用，这可以通过基于路径和网络的数据分析最好地实现，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.