Analysis of complex biological systems by high-throughput genomic technologies

计算生物学和基因组学核心(CBGC)旨在通过下一代测序、单细胞测序和微阵列等高通量基因组技术分析复杂生物系统，推进NIA-IRP的衰老研究。CBGC主要向NIA内部科学家及其合作者提供这些服务。此外，我们还与其他NIH研究所以及校外社区的研究人员直接合作。在2020财年，我们完成了1458个样本的测序，完成了218个RNA样本的微阵列杂交。 计算生物学和基因组学核心(CBGC)提供关于实验设计和样品准备、样品质量控制、数据分析、数据共享和培训的建议。除了主要专注于基因组和转录组研究外，CBGC还对将人工智能(AI)应用于图像分析和新的基因组数据分析算法非常感兴趣。该核心利用基因表达微阵列、Illumina和牛津纳米孔测序仪以及10倍基因组单细胞分析仪器来满足NIA IRP研究人员的需求。此外，CBGC维护多个高性能计算机系统，并参与设计和维护NIA IRP云计算，供所有感兴趣的NIA IRP研究人员使用。

Computational Biology & Genomics Core (CBGC) aims to advance aging research in NIA-IRP through the analysis of complex biological systems by high-throughput genomic technologies such as Next Generation Sequencing, Single Cell Sequencing, and microarrays. CBGC provides these services primarily to NIA intramural scientists and their collaborators. In addition, we collaborate directly with investigators in other NIH institutes as well as the extramural community. In fiscal year 2020 we completed sequencing of 1458 samples and completed microarray hybridization of 218 RNA samples. The Computational Biology & Genomics Core (CBGC) provides advice on experimental design and sample preparation, quality control of samples, data analysis, data sharing, and training. Apart from the primary focus on genomic and transcriptomic research, CBGC is highly interested in applying Artificial Intelligence (AI) for image analysis and novel genomic data analysis algorithms. The core utilizes gene expression microarrays, Illumina and Oxford Nanopore sequencers and 10x Genomics single-cell analysis instruments to meet the needs of NIA IRP researchers. Moreover, CBGC maintains several high-performance computer systems and is involved in designing and maintaining NIA IRP cloud computing for use by all interested NIA IRP researchers.