Teo Yong-Meng, Wang Xianbing, Ng Yew-Kwong
Department of Computer Science, National University of Singapore, Singapore 117543.
Bioinformatics. 2005 Mar;21(6):794-802. doi: 10.1093/bioinformatics/bti034. Epub 2004 Sep 23.
Grid computing is used to solve large-scale bioinformatics problems with gigabytes database by distributing the computation across multiple platforms. Until now in developing bioinformatics grid applications, it is extremely tedious to design and implement the component algorithms and parallelization techniques for different classes of problems, and to access remotely located sequence database files of varying formats across the grid. In this study, we propose a grid programming toolkit, GLAD (Grid Life sciences Applications Developer), which facilitates the development and deployment of bioinformatics applications on a grid.
GLAD has been developed using ALiCE (Adaptive scaLable Internet-based Computing Engine), a Java-based grid middleware, which exploits the task-based parallelism. Two bioinformatics benchmark applications, such as distributed sequence comparison and distributed progressive multiple sequence alignment, have been developed using GLAD.
网格计算通过在多个平台上分布计算来解决具有千兆字节数据库的大规模生物信息学问题。到目前为止,在开发生物信息学网格应用程序时,针对不同类型的问题设计和实现组件算法及并行化技术,以及跨网格远程访问不同格式的位于远程的序列数据库文件,都极其繁琐。在本研究中,我们提出了一个网格编程工具包GLAD(网格生命科学应用程序开发者工具包),它有助于在网格上开发和部署生物信息学应用程序。
GLAD是使用ALiCE(基于自适应可扩展互联网的计算引擎)开发的,ALiCE是一个基于Java的网格中间件,它利用基于任务的并行性。使用GLAD开发了两个生物信息学基准应用程序,如分布式序列比较和分布式渐进多序列比对。