Applied Bioinformatics Laboratories Shared Resource

摘要/项目摘要 应用生物信息学实验室(ABL) 应用生物信息学实验室(ABL)的首要目标是提供强大的、 具有成本效益、快速和可重复的生物医学数据分析，包括但不限于 多组学、影像和临床数据。这一目标是通过使用各种 建立和创新的计算工作流程、方法和工具。在……的领导下 ABL的Aristotelis Tsirigos博士提供了测序分析的全程标准化 数据集、严格的数据质量评估、集成和可视化以及统计 与生物统计共享资源(BioStat)密切合作的专门知识。ABL也有效 与其他PCC共享资源密切合作，最著名的是基因组技术中心和 生物质学家研究与开发中心。生物信息学分析的结果 通过定制的界面与PCC调查人员共享在ABL进行的工作，还 可通过高性能计算(HPC)群集访问。超越数据管理和 分析，ABL通过三个具体目标为研究周期的所有方面作出贡献： 目标1)为PCC产生的生物医学数据提供统一和简化的分析 调查人员；目标2)管理和传播生物信息学分析的数据和结果； 目的3)利用数据集成和机器学习方法产生新的见解和 假设。

Abstract/Project Summary APPLIED BIOINFORMATICS LABORATORIES (ABL) The overarching goal of the Applied Bioinformatics Laboratories (ABL) is to provide robust, cost-effective, rapid and reproducible analysis of biomedical data, including, but not limited to multi-omics, imaging and clinical data. This goal is accomplished by using a variety of established and novel computational workflows, methods and tools. Under the directorship of Dr. Aristotelis Tsirigos, ABL provides start-to-finish standardization of the analysis of sequencing datasets, rigorous data quality assessment, integration and visualization, as well as statistical expertise in close collaboration with the Biostatistics shared resource (Biostat). ABL also works closely with other PCC shared resources, most notably the Genome Technology Center and the Center for Biospecimen Research and Development. The results of the bioinformatics analyses conducted in ABL are shared with PCC investigators via a customized interface and are also accessible via the High-Performance Computing (HPC) cluster. Beyond data management and analysis, ABL contributes to all aspects of the research cycle by means of three Specific Aims: Aim 1) To provide unified and streamlined analysis of biomedical data generated by PCC investigators; Aim 2) To manage and disseminate data and results of bioinformatics analyses; Aim 3) To utilized data integration and machine learning methods to generate new insights and hypotheses.