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Related Experiment Videos

Pluggable application server framework.

H Wang1, F Tan, A Sabnis

  • 1Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA 30303, USA.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
PubMed
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This study introduces a pluggable framework for integrating diverse software components, simplifying complex system construction for protein structure prediction. The adaptable design allows for rapid, code-free integration of heterogeneous programs, enhancing system efficiency and configurability.

Area of Science:

  • Computational Biology
  • Software Engineering
  • Bioinformatics

Background:

  • Integrating disparate software components for complex tasks like protein structure prediction is challenging due to a lack of inherent interoperability.
  • Existing systems often require significant code modification to incorporate new or existing programs.

Purpose of the Study:

  • To present a novel pluggable application server framework designed for seamless integration of heterogeneous computational components.
  • To enable rapid and efficient system construction for protein structure prediction without altering source code of individual programs.

Main Methods:

  • Development of a pluggable application server framework based on a generic integration model.
  • Configuration-driven component integration, allowing easy addition of diverse programs.

Related Experiment Videos

  • Implementation of a protein structure prediction server utilizing the developed framework.

    • Main Results:

    • Demonstrated a framework capable of efficiently combining various existing programs into a cohesive system.
    • Achieved a self-configurable and adaptive system through easy component plugging and configuration.
    • Successfully implemented a protein structure prediction server highlighting system construction efficiency and simplicity.

    Conclusions:

    • The proposed framework provides a generic and adaptable solution for integrating heterogeneous software components.
    • The model facilitates rapid system development and can be applied beyond protein structure prediction to other domains.
    • The approach simplifies complex system construction, emphasizing efficiency and ease of use.