Computer cluster for computational biology

计算生物学计算机集群

• 批准号: 6877645
• 负责人: Ron Elber
• 金额: $ 50万
• 依托单位: CORNELL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2006-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6877645
• 关键词: bioinformatics; biomedical equipment purchase; computational biology; computer network; computer program /software; computer system hardware; computers

DESCRIPTION (provided by applicant): The present application aims to establish a computer Cluster for Computational Biology and Bioinformatic (CCBB). The cluster will consists of 256 dual nodes connected with Giganet switches to enable rapid communication between the processors. The cluster will enable the integration of the two approaches and make it possible to effectively address the highly demanding computational tasks of the field. It will serve a small group of investigators, supported by the NIH, and their close collaborators. The hardware needs of computational biology and bioinformatic applications, and of the team of investigators listed in this application can be summarized as follows: 1. Significant computer power for complex and expensive simulations. 2. Large storage capacity for the whole cluster (shared) and (separately) for the individual nodes. 3. Large and rapidly accessible memory for effective statistical analysis, application of machine learning techniques, and biological discovery. 4. Fast network for information updates across the network. In addition CCBB will have high level of databases and software integration including 1. Updates of important "mirrors" of shared databases (such as NR, swissprot, human EST, human genome, protein databank, etc.) 2. Local installation and frequent upgrade of widely used software packages (e.g. BLAST, Pfam, CHARMm etc.) 3. Help in porting novel software for optimal use on the CCBB hardware platform. The combined unification of optimal hardware and software for computational biology and bioinformatic will make the new cluster; an outstanding resource for NIH related research

描述（由申请人提供）： 本申请旨在建立计算生物学和生物信息学计算机集群（CCBB）。该集群将由 256 个双节点组成，这些节点通过 Giganet 交换机连接，以实现处理器之间的快速通信。该集群将实现两种方法的集成，并能够有效地解决该领域高要求的计算任务。它将为一小群研究人员提供服务，并得到 NIH 及其密切合作者的支持。计算生物学和生物信息学应用以及本申请中列出的研究人员团队的硬件需求可总结如下： 1. 强大的计算机能力可用于复杂且昂贵的模拟。 2.整个集群（共享）和单个节点（单独）的大存储容量。 3. 大容量且可快速访问的内存，用于有效的统计分析、机器学习技术的应用和生物发现。 4.网络速度快，信息全网更新。 此外，CCBB 将拥有高水平的数据库和软件集成，包括 1、共享数据库重要“镜子”更新（如NR、swissprot、人类EST、人类基因组、蛋白质数据库等） 2.广泛使用的软件包（例如BLAST、Pfam、CHARMm等）的本地安装和频繁升级 3. 帮助移植新颖的软件，以便在CCBB硬件平台上得到最佳使用。 计算生物学和生物信息学的最佳硬件和软件的组合统一将形成新的集群； NIH 相关研究的杰出资源

项目成果

Apples to apples: improving the performance of motif finders and their significance analysis in the Twilight Zone.

苹果到苹果：提高主题查找器的性能及其在暮光区的意义分析。

• 发表时间: 2006-07-15
• 作者: Ng, Patrick;Nagarajan, Niranjan;Jones, Neil;Keich, Uri
• 通讯作者: Keich, Uri

Factoring local sequence composition in motif significance analysis.

在基序重要性分析中考虑局部序列组成。

• 发表时间: 2008
• 作者: Ng, Patrick;Keich, Uri
• 通讯作者: Keich, Uri

Computational detection of significant variation in binding affinity across two sets of sequences with application to the analysis of replication origins in yeast.

计算检测两组序列之间结合亲和力的显着变化，并应用于酵母复制起点的分析。

• 发表时间: 2008
• 影响因子: 3
• 作者: Keich, Uri;Gao, Hong;Garretson, Jeffrey S;Bhaskar, Anand;Liachko, Ivan;Donato, Justin;Tye, Bik K
• 通讯作者: Tye, Bik K

The network of sequence flow between protein structures.

蛋白质结构之间的序列流网络。

• 发表时间: 2007-07-10
• 影响因子: 11.1
• 作者: Meyerguz, Leonid;Kleinberg, Jon;Elber, Ron
• 通讯作者: Elber, Ron