Bioportal: a portal for deployment of bioinformatics applications on cluster and grid environments

  • Authors:

  • Kuan-Ching Li;Chiou-Nan Chen;Tsung-Ying Wu;Chia-Hsien Wen;Chuan Yi Tang

  • Affiliations:

  • Parallel and Distributed Processing Center, Department of Computer Science and Information Engineering, Providence University Shalu, Taichung, Taiwan;Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan;Grid Operation Center, National Center for High-Performance Computing, Taichung, Taiwan;Department of Computer Science and Information Management, Providence University Shalu, Taichung, Taiwan;Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan

  • Venue:
  • VECPAR'06 Proceedings of the 7th international conference on High performance computing for computational science
  • Year:
  • 2006

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Abstract

Over last few years, interest on biotechnology has increased dramatically. With the completion of sequencing of the human genome, such interest is likely to expand even more rapidly. The size of genetic information database doubles every 14 months, overwhelming explosion of information in related bioscience disciplines and consequently, overtaxing any existing computational tool for data analysis. There is a persistent and continuous search for new alternatives or new technologies, all with the common goal of improving overall computational performance. Grid infrastructures are characterized by interconnecting a number of heterogeneous hosts through the internet, by enabling large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. In this research paper, we present BioPortal, a user friendly and web-based GUI that eases the deployment of well-known bioinformatics applications on large-scale cluster and grid computing environments. The major motivation of this research is to enable biologists and geneticists, as also biology students and investigators, to access to high performance computing without specific technical knowledge of the means in which are handled by these computing environments and no less important, without introducing any additional drawback, in order to accelerate their experimental and sequence data analysis. As result, we could demonstrate the viability of such design and implementation, involving solely freely available softwares.