Analysis of complex biological systems by high-throughput genomic technologies

通过高通量基因组技术分析复杂的生物系统

• 批准号: 10913226
• 负责人: Supriyo De
• 金额: $ 32.21万
• 依托单位: NATIONAL INSTITUTE ON AGING
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10913226
• 关键词: Aging; Algorithmic Analysis; Artificial Intelligence; CRISPR screen; Cells; Cloud Computing; Collaborations; Communities; Computational Biology; Computer Systems; Data Analyses; Data Scientist; Experimental Designs; Extramural Activities; Fostering; Gene Chips; Genomics; Goals; Image Analysis; Interdisciplinary Study; Laboratories; Mission; Preparation; Quality Control; Research; Research Personnel; Sampling; Scientist; Services; Technology; Training; United States National Institutes of Health; biomedical data science; complex biological systems; data sharing; design; epigenomics; functional genomics; genomic data; high end computer; instrument; interest; nanopore; next generation sequencing; novel; programs; single cell analysis; single cell sequencing; transcriptomics

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 past year we completed sequencing of over 2400 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.

计算生物学和基因组学核心（CBGC）旨在通过高通量基因组技术（如下一代测序，单细胞测序和微阵列）分析复杂的生物系统，推进NIA-IRP中的衰老研究。CBGC主要向NIA内部科学家及其合作者提供这些服务。此外，我们直接与其他NIH研究所以及校外社区的研究人员合作。在过去的一年里，我们完成了2400多个样本的测序。 计算生物学和基因组学核心（CBGC）提供有关实验设计和样品制备，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学研究外，CBGC对将人工智能（AI）应用于图像分析和新型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Oxford Nanopore测序仪以及10 x Genomics单细胞分析仪器来满足NIA IRP研究人员的需求。此外，CBGC维护了几个高性能的计算机系统，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。

项目成果

Gene expression and pathway analysis of ovarian cancer cells selected for resistance to cisplatin, paclitaxel, or doxorubicin.

• DOI: 10.1186/1757-2215-4-21
• 发表时间: 2011-12-05
• 期刊: Journal of ovarian research
• 影响因子: 4
• 作者: Sherman-Baust CA;Becker KG;Wood Iii WH;Zhang Y;Morin PJ
• 通讯作者: Morin PJ

DNA repair and the accumulation of oxidatively damaged DNA are affected by fruit intake in mice.

小鼠的 DNA 修复和氧化损伤 DNA 的积累受到水果摄入量的影响。

• DOI: 10.1093/gerona/glq157
• 发表时间: 2010
• 期刊: The journals of gerontology. Series A, Biological sciences and medical sciences
• 作者: Croteau,DeborahL;deSouza-Pinto,NadjaC;Harboe,Charlotte;Keijzers,Guido;Zhang,Yongqing;Becker,Kevin;Sheng,Shan;Bohr,VilhelmA
• 通讯作者: Bohr,VilhelmA

Extracellular RNA profiles with human age.

• DOI: 10.1111/acel.12785
• 发表时间: 2018-08
• 期刊: Aging cell
• 影响因子: 7.8
• 作者: Dluzen DF;Noren Hooten N;De S;Wood WH 3rd;Zhang Y;Becker KG;Zonderman AB;Tanaka T;Ferrucci L;Evans MK
• 通讯作者: Evans MK

Survey of the Arc Epigenetic Landscape in Normal Cognitive Aging.

• DOI: 10.1007/s12035-020-01915-4
• 发表时间: 2020-06
• 期刊: Molecular neurobiology
• 影响因子: 5.1
• 作者: Myrum C;Kittleson J;De S;Fletcher BR;Castellano J;Kundu G;Becker KG;Rapp PR
• 通讯作者: Rapp PR

Amitriptyline-mediated cognitive enhancement in aged 3×Tg Alzheimer's disease mice is associated with neurogenesis and neurotrophic activity.

• DOI: 10.1371/journal.pone.0021660
• 发表时间: 2011
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Chadwick W;Mitchell N;Caroll J;Zhou Y;Park SS;Wang L;Becker KG;Zhang Y;Lehrmann E;Wood WH 3rd;Martin B;Maudsley S
• 通讯作者: Maudsley S