Beagle-2

小猎犬2号

• 批准号: 8734865
• 负责人: Ian Foster
• 金额: $ 199.98万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8734865
• 关键词: Alzheimer' s Disease; Area; Big Data; Biological Sciences; Biomedical Computing; Biomedical Research; Brain; Cardiovascular Diseases; Cellular biology; Chicago; Collaborations; Communities; Data; Data Analyses; Data Storage and Retrieval; Disease; Drug Design; Educational workshop; Faculty; Funding; Genetic; Hour; Human; Investments; Language; Life; Malignant Neoplasms; Medical Imaging; Medical Research; Methods; Microbiology; Myopathy; Neurosciences; Patient Care; Postdoctoral Fellow; Research; Research Personnel; Resources; Scientist; Services; Software Tools; Students; Supercomputing; System; Time; Training; United States National Institutes of Health; Universities; Work; biological research; cancer cell; cancer genetics; frontier; large scale simulation; next generation; supercomputer

DESCRIPTION: Biomedical research increasingly depends on big data analysis and large-scale simulation. In 2009, the University of Chicago's Biological Sciences Division identified computational biomedicine as its major strategic focus for research, recruitment and strategic investment. The centerpiece of this initiative was the acquisition of Beagle-1, an 18,000-core, 600 TB supercomputer that ranked among the world's most powerful machines dedicated to biological and medical research. Since its debut in early 2011, more than 300 researchers from 89 projects have used Beagle-1, utilizing over 300 million core-hours of computing time. With Beagle-1, scientists pushed forward the frontiers of research on cancer, neuroscience, genetics, cardiovascular disease, microbiology, drug design, and other areas. Work conducted on Beagle-1 also sparked the emergence of a vibrant computational biomedicine community on the University Chicago campus and across the Chicago region, where faculty, post-docs, students and staff benefit from frequent workshops, seminars and educational opportunities. The surge in demand for biomedical supercomputing concomitant with Beagle-1 approaching the end of its life necessitates the acquisition of a new, more powerful resource: Beagle-2, a 23,808-core, 1.3 petabyte Cray XE6 system. This major upgrade will increase computational and big data storage capabilities by two fold while also delivering service for researchers through 2017. An estimated 150 million core hours per year for this system can already be filled by active, NIH-funded projects studying the genetics of cancer and myopathies, the microbiology of the human gut and its relationship to disease, the use of medical images to create personalized treatments for cancer, the cell biology of Alzheimer's disease, the evolutionary origins of language centers in the brain, and much more. Beagle-2 will allow the University of Chicago to further develop a biomedical computing facility that enhances research and patient care, trains the next generation of biomedical computing experts, enables collaboration by researchers across the Chicago region and beyond, and produces transformative new methods, software tools, and data products that will advance biomedical research on a global scale.

生物医学研究越来越依赖于大数据分析和大规模模拟。2009年，芝加哥大学生物科学系将计算生物医学确定为研究、招聘和战略投资的主要战略重点。该计划的核心是收购Beagle-1，这是一台18，000核，600 TB的超级计算机，是世界上最强大的生物和医学研究机器之一。自2011年初首次亮相以来，来自89个项目的300多名研究人员使用了Beagle-1，利用了超过3亿核心小时的计算时间。通过Beagle-1，科学家们推进了癌症、神经科学、遗传学、心血管疾病、微生物学、药物设计和其他领域的研究前沿。在Beagle-1上进行的工作还引发了芝加哥大学校园和整个芝加哥地区充满活力的计算生物医学社区的出现，教师，博士后，学生和工作人员从频繁的研讨会，研讨会和教育机会中受益。随着Beagle-1生命周期的结束，对生物医学超级计算的需求激增，需要收购一个新的，更强大的资源：Beagle-2，一个23，808核，1.3 PB的Cray XE 6系统。这一重大升级将使计算和大数据存储能力提高两倍，同时在2017年之前为研究人员提供服务。据估计，该系统每年的1.5亿核心小时已经可以由NIH资助的积极项目填补，这些项目研究癌症和肌病的遗传学，人类肠道的微生物学及其与疾病的关系，使用医学图像创建个性化治疗癌症，阿尔茨海默病的细胞生物学，大脑语言中心的进化起源等等。Beagle-2将使芝加哥大学能够进一步开发生物医学计算设施，以增强研究和患者护理，培训下一代生物医学计算专家，实现芝加哥地区及其他地区研究人员的合作，并产生变革性的新方法、软件工具和数据产品，以推动全球范围内的生物医学研究。

项目成果

A c-Myc-regulated stem cell-like signature in high-risk neuroblastoma: A systematic discovery (Target neuroblastoma ESC-like signature).

• DOI: 10.1038/s41598-017-00122-x
• 发表时间: 2017-03-03
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Yang XH;Tang F;Shin J;Cunningham JM
• 通讯作者: Cunningham JM

High-throughput cancer hypothesis testing with an integrated PhysiCell-EMEWS workflow

• DOI: 10.1186/s12859-018-2510-x
• 发表时间: 2018-12-21
• 期刊: BMC BIOINFORMATICS
• 影响因子: 3
• 作者: Ozik, Jonathan;Collier, Nicholson;Macklin, Paul
• 通讯作者: Macklin, Paul

The Crisis of Reproducibility, the Denominator Problem and the Scientific Role of Multi-scale Modeling.

• DOI: 10.1007/s11538-018-0497-0
• 发表时间: 2018-12
• 期刊: Bulletin of mathematical biology
• 影响因子: 3.5
• 作者: An G

Scaled laboratory experiments explain the kink behaviour of the Crab Nebula jet.

• DOI: 10.1038/ncomms13081
• 发表时间: 2016-10-07
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Li, C. K.;Tzeferacos, P.;Lamb, D.;Gregori, G.;Norreys, P. A.;Rosenberg, M. J.;Follett, R. K.;Froula, D. H.;Koenig, M.;Seguin, F. H.;Frenje, J. A.;Rinderknecht, H. G.;Sio, H.;Zylstra, A. B.;Petrasso, R. D.;Amendt, P. A.;Park, H. S.;Remington, B. A.;Ryutov, D. D.;Wilks, S. C.;Betti, R.;Frank, A.;Hu, S. X.;Sangster, T. C.;Hartigan, P.;Drake, R. P.;Kuranz, C. C.;Lebedev, S. V.;Woolsey, N. C.
• 通讯作者: Woolsey, N. C.

Nested active learning for efficient model contextualization and parameterization: pathway to generating simulated populations using multi-scale computational models.

• DOI: 10.1177/0037549720975075
• 发表时间: 2021-04
• 期刊: Simulation
• 作者: Cockrell C;Ozik J;Collier N;An G
• 通讯作者: An G