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Supercomputing: Rutgers' Catalyst for Discovery at the Frontiers of Medicine

超级计算：罗格斯大学医学前沿发现的催化剂

基本信息

批准号：
8734820
负责人：
Leslie Paul Michelson
金额：
$ 171.71万
依托单位：
RBHS-NEW JERSEY MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-03-01 至 2016-02-29
项目状态：
已结题

项目摘要

DESCRIPTION: The University of Medicine and Dentistry of New Jersey (UMDNJ) and Rutgers University were joined by an act of the State Legislature, effective July 1, 2013. This newly enlarged Rutgers University integrates the medical and dental specialists from UMDNJ into a world-class biomedical research institution. Our researchers across the departments of Medicine, Biology, Genetics, Chemistry, Math, Pharmacology, Biochemistry, Chemical and Biochemical Engineering, Molecular Biology and Obstetrics are involved in well-funded research projects that have a need for a large computational resource. In total, these researchers have 64 NIH-funded grants with total annual direct costs of > $60M. Many of the investigators are struggling to perform their calculations on the limited computational resources that are currently at our disposal. Other researchers are not able to realize the full potential of their research due to the lack of sufficient computation. For example, some molecular dynamics simulations will produce more realistic results if the system could be modeled for intervals of up to 1 microsecond, but the limit with our current infrastructure is tens of nanoseconds per month for most systems. As another example, genomics researchers have hundreds of exomes and RNA-seq samples that need to be processed and analyzed, but the research is moving at a slow pace due to the bottle-neck of the analysis pipeline. We are proposing a cluster with 2,800 computational cores, 128GB of RAM per compute node and 465TB of storage in a state-of- the-art, energy efficient, cluster configuration. The use, also, of very fast node interconnects (FDR Infiniband) provides the appropriate fabric for problems that are highly scalable, such as molecular dynamics and docking while at the same time supporting the execution of thousands of individual serial jobs. The new computational cluster will enhance the research of our investigators, taking it to levels unattainable with existing resources. This computational cluster will set a new paradigm for a large-scale, centrally managed resource supporting a broad spectrum of biomedical research.

产品说明：新泽西医学和牙科大学（UMDNJ）和罗格斯大学加入了州议会的一项法案，于2013年7月1日生效。这个新扩大的罗格斯大学将UMDNJ的医学和牙科专家整合为世界级的生物医学研究机构。我们在医学，生物学，遗传学，化学，数学，药理学，生物化学，化学和生物化学工程，分子生物学和产科部门的研究人员都参与了资金充足的研究项目，需要大量的计算资源。总的来说，这些研究人员有64个NIH资助的赠款，每年的直接费用总额超过6000万美元。许多研究人员正在努力在我们目前可支配的有限计算资源上进行计算。其他研究人员无法实现其研究的全部潜力，缺乏足够的计算。例如，一些分子动力学模拟将产生更现实的结果，如果系统可以建模的间隔高达1微秒，但我们目前的基础设施的限制是几十纳秒每月为大多数系统。作为另一个例子，基因组学研究人员有数百个外显子组和RNA-seq样本需要处理和分析，但由于分析管道的瓶颈，研究进展缓慢。我们提出的群集具有2，800个计算核心，每个计算节点128 GB RAM和465 TB存储，采用最先进的节能群集配置。此外，使用非常快速的节点互连（FDR Infiniband）为高度可扩展的问题提供了适当的结构，例如分子动力学和对接，同时支持执行数千个单独的串行作业。新的计算集群将增强我们研究人员的研究，将其提升到现有资源无法达到的水平。这个计算集群将为支持广泛的生物医学研究的大规模集中管理资源树立一个新的典范。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Reversible gene silencing through frameshift indels and frameshift scars provide adaptive plasticity for Mycobacterium tuberculosis.

DOI：
10.1038/s41467-021-25055-y
发表时间：
2021-08-04
期刊：
Nature communications
影响因子：
16.6
作者：
Gupta A;Alland D
通讯作者：
Alland D

The β1'-β2' Motif of the RNase H Domain of Human Immunodeficiency Virus Type 1 Reverse Transcriptase Is Responsible for Conferring Open Conformation to the p66 Subunit by Displacing the Connection Domain from the Polymerase Cleft.

人类免疫缺陷病毒 1 型逆转录酶的 RNase H 结构域的 β1-β2 基序负责通过置换聚合酶裂口的连接结构域来赋予 p66 亚基开放构象。

DOI：
10.1021/acs.biochem.7b00005
发表时间：
2017
期刊：
Biochemistry
影响因子：
2.9
作者：
Pandey,AshutoshK;Dixit,Updesh;Kholodovych,Vlad;Comollo,ThomasW;Pandey,VirendraN
通讯作者：
Pandey,VirendraN

Self-assembled cationic amphiphiles as antimicrobial peptides mimics: Role of hydrophobicity, linkage type, and assembly state.