High-performance compute cluster for biomedical computing

用于生物医学计算的高性能计算集群

• 批准号: 8334997
• 负责人: ANDREA CALIFANO
• 金额: $ 200万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8334997
• 关键词: Address; Algorithms; Binding; Bioinformatics; Biological; Biomedical Computing; Biomedical Research; Budgets; Communities; Computational Biology; Computers; Consumption; DNA; DNA-Binding Proteins; Data; Data Analyses; Data Set; Dissection; Environment; Equipment; Faculty; Funding; Future; Genome; Glioma; Grant; High Performance Computing; Hour; Investigation; Investments; Lymphoma; Mesenchymal; Methodology; Mission; Nature; New York; Performance; Phenotype; Process; Recruitment Activity; Research; Research Infrastructure; Research Personnel; Role; Running; Shapes; Software Tools; Specificity; System; Systems Biology; Titan; United States National Institutes of Health; Universities; base; combinatorial; gene discovery; gene interaction; malignant phenotype; melanoma; novel; programs; success

DESCRIPTION (provided by applicant): The Center for Computational Biology and Bioinformatics (C2B2) was established in 2003, with the mission of providing the biomedical research community with Structural and Systems Biology algorithms and software tools for the dissection of molecular interactions and for the interaction-based elucidation of cellular phenotypes. Over the last few years C2B2 investigators have developed many novel analysis methodologies which have led to important biological discoveries including understanding the role of DNA shape in protein- DNA binding specificity and the discovery of genes causally related to the presentation of malignant phenotypes, including Lymphoma, Glioma, and Melanoma. A common thread among all these computational investigations is their very significant computational requirements. This is a result of both the combinatorial nature of the algorithms as well as the genome-scale size of the data sets on which they are being applied. For example, more than 1 million CPU-hours were needed to generate the gene interaction network that was used to identify the master regulators that drive the mesenchymal phenotype in Glioma. In practical terms, such investigations are only feasible when carried out on a high performance computing (HPC) environment. To address this need, C2B2 has made significant investments in high performance IT infrastructure (utilizing grants from Columbia University, the New York State and the NIH) and has assembled one of the largest HPC facilities dedicated to biological investigation in the nation. The centerpiece of the C2B2 HPC infrastructure is Titan, a 3712 core cluster which was ranked by Top500.org as the 124th fastest computer in the world when the system debuted in 2008. This infrastructure has been instrumental to the success of C2B2, by enabling Center researchers to execute computational investigations that would have otherwise been infeasible and by allowing us to recruit and retain world class faculty. As has been the case in the past, we have now reached a point where the computational needs of our investigators are exceeding the limits of our HPC infrastructure. Historical utilization data demonstrate that computation consumption has been doubling annually. As a result, Titan has been running at its peak capacity for the past six to eight months. We anticipate that demand for computation will increase even further as C2B2 is in the process of transitioning from a Center to a full University Department (Dept. of Systems Biology) with approved budget for 9 more faculty hires. Through this application we seek to quadruple our computational capacity to accommodate the data analysis needs of several NIH funded projects over a period of 2-3 years. Given the central role of computing in the research program of C2B2, the availability of an adequate and easily accessible HPC environment is a critical prerequisite for the successful completion of these projects. The equipment purchase requested here will allow us to continue serving the needs of biomedical research at Columbia University for the foreseeable future.

描述（由申请人提供）：计算生物学和生物信息学中心（C2 B2）成立于2003年，其使命是为生物医学研究社区提供结构和系统生物学算法和软件工具，用于分子相互作用的解剖和基于相互作用的细胞表型的阐明。在过去的几年中，C2 B2研究人员已经开发了许多新的分析方法，这些方法已经导致了重要的生物学发现，包括理解DNA形状在蛋白质- DNA结合特异性中的作用，以及发现与恶性表型（包括淋巴瘤、胶质瘤和黑素瘤）的呈现有因果关系的基因。所有这些计算研究中的一个共同点是它们非常重要的计算要求。这是算法的组合性质以及它们所应用的数据集的基因组规模大小的结果。例如，需要超过100万CPU小时来生成基因相互作用网络，该网络用于识别驱动胶质瘤中间充质表型的主调节因子。 实际上，这种调查只有在高性能计算（HPC）环境中进行时才可行。为了满足这一需求，C2 B2在高性能IT基础设施方面进行了大量投资（利用哥伦比亚大学、纽约州和NIH的赠款），并组建了全国最大的HPC设施之一，专门用于生物研究。C2 B2 HPC基础设施的核心是Titan，这是一个3712核心的集群，在2008年首次亮相时被Top500.org评为世界上第124快的计算机。这种基础设施有助于C2 B2的成功，使中心的研究人员能够执行计算调查，否则将是不可行的，并允许我们招募和留住世界一流的教师。 与过去的情况一样，我们现在已经达到了一个点，我们的调查人员的计算需求超过了我们的HPC基础设施的限制。历史利用率数据表明，计算消耗每年翻一番。因此，在过去的六到八个月里，泰坦一直在以最大的能力运行。我们预计，随着C2 B2正在从一个中心过渡到一个完整的大学系（系），对计算的需求将进一步增加。系统生物学），并批准了再雇用9名教师的预算。通过这个应用程序，我们寻求我们的计算能力翻两番，以适应几个NIH资助的项目在2-3年内的数据分析需求。考虑到计算在C2 B2研究计划中的核心作用，提供一个足够且易于访问的HPC环境是成功完成这些项目的关键先决条件。这里要求购买的设备将使我们能够在可预见的未来继续为哥伦比亚大学的生物医学研究提供服务。

项目成果

Gene-Specific Substitution Profiles Describe the Types and Frequencies of Amino Acid Changes during Antibody Somatic Hypermutation.

• DOI: 10.3389/fimmu.2017.00537
• 发表时间: 2017
• 期刊: Frontiers in immunology
• 影响因子: 7.3
• 作者: Sheng Z;Schramm CA;Kong R;NISC Comparative Sequencing Program;Mullikin JC;Mascola JR;Kwong PD;Shapiro L
• 通讯作者: Shapiro L

De novo missense variants in PPP2R5D are associated with intellectual disability, macrocephaly, hypotonia, and autism.

• DOI: 10.1007/s10048-015-0466-9
• 发表时间: 2016-01
• 期刊: Neurogenetics
• 影响因子: 2.2
• 作者: Shang L;Henderson LB;Cho MT;Petrey DS;Fong CT;Haude KM;Shur N;Lundberg J;Hauser N;Carmichael J;Innis J;Schuette J;Wu YW;Asaikar S;Pearson M;Folk L;Retterer K;Monaghan KG;Chung WK
• 通讯作者: Chung WK

Erratum to: HDAC6 activity is a non-oncogene addiction hub for inflammatory breast cancers.

勘误表：HDAC6 活性是炎症性乳腺癌的非癌基因成瘾中心。

• DOI: 10.1186/s13058-017-0841-6
• 发表时间: 2017
• 期刊: Breast cancer research : BCR
• 作者: Putcha,Preeti;Yu,Jiyang;Rodriguez-Barrueco,Ruth;Saucedo-Cuevas,Laura;Villagrasa,Patricia;Murga-Penas,Eva;Quayle,StevenN;Yang,Min;Castro,Veronica;Llobet-Navas,David;Birnbaum,Daniel;Finetti,Pascal;Woodward,WendyA;Bertucci,Franço
• 通讯作者: Bertucci,Franço