• DocumentCode
    3078142
  • Title

    A Framework to Accelerate Protein Structure Comparison Tools

  • Author

    Salah, Ahmad ; Kneli Li ; Gharib, Tarek F.

  • Author_Institution
    Coll. of Comput. Sci. & Electron. Eng., Hunan Univ., Changsha, China
  • fYear
    2015
  • fDate
    4-7 May 2015
  • Firstpage
    705
  • Lastpage
    708
  • Abstract
    At the center of computational structural biology, protein structure comparison is a key problem. The steady increase in the number of protein structures encourages the development of massively parallel tools. While the focus of research is to propose data-analytical methods to tackle this problem, there are limited research proposing generic tools to run these methods in parallel environments. Herein, we propose a scalable framework to handle this steady increase. The proposed framework runs the sequential tools on parallel environments. It is a GUI-based and requiring no scripting or installation procedures. The framework includes optimally distributing protein structure database over the existing computing resources, tracking the remote processes course of execution, and merging the results to form the final output. The first stage realizes the biological database distribution as an optimization problem in order to maximize the cluster resources utilization and minimize the execution time. The experimental results show linear and nearly optimal speedups with no loss in accuracy. The framework is available at http://biocloud.hnu.edu.cn/ppsc/.
  • Keywords
    bioinformatics; distributed databases; graphical user interfaces; minimisation; parallel processing; pattern clustering; proteins; GUI-based procedure; biological database distribution; computational structural biology; data-analytical methods; execution time minimization; generic tools; massively parallel tools; optimally-distributing protein structure database; optimization problem; parallel environments; protein structure comparison tool; remote processes; resources utilization maximization; scalable framework; Accuracy; Computational modeling; Databases; Optimization; Parallel processing; Proteins; Protein structure comparison; grid; multicore; parallel framework; speedup;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/CCGrid.2015.136
  • Filename
    7152537