Multiple sequence alignments with regular expression constraints on a cloud service system

Yu Shiang Lin, Chun Yuan Lin, Hsiao Chieh Chi, Yeh Ching Chung

    Research output: Contribution to journalJournal Article peer-review

    1 Scopus citations

    Abstract

    Multiple sequence alignments with constraints are of priority concern in computational biology. Constrained sequence alignment incorporates the domain knowledge of biologists into sequence alignments such that the user-specified residues/segments are aligned together according to the alignment results. A series of constrained multiple sequence alignment tools have been developed in relevant literatures in the recent decade. GPU-REMuSiC is the most advanced method with the regular expression constraints, in which graphics processing units (GPUs) with CUDA are used. GPU-REMuSiC can achieve a speedup ratio of 29x for overall computation time based on the experimental results. However, the execution environment of GPU-REMuSiC must be constructed; it is a threshold for biologists to set up it. Therefore, this work presents an intuitive friendly user interface of GPU-REMuSiC for the potential cloud server with GPUs, called Cloud GPU-REMuSiC. Implementing the user interface via a network allows us to transmit the input data to a remote server without a complex cumbersome setting in a local host. Finally, the alignment results can be obtained from a remote cloud server with GPUs. Cloud GPU-REMuSiC is highly promising as an online application that is accessible without time or location constraints.

    Original languageEnglish
    Pages (from-to)55-64
    Number of pages10
    JournalInternational Journal of Grid and High Performance Computing
    Volume5
    Issue number3
    DOIs
    StatePublished - 2013

    Keywords

    • CUDA
    • Cloud computing
    • Dynamic programming
    • Graphics processing units (GPUs)
    • Multiple sequence alignments
    • Parallel processing
    • Regular expression
    • User interface

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