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Object-oriented biological system integration: a SARS coronavirus example.

Daniel Shegogue1, W Jim Zheng

  • 1Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon Street, PO Box 250835, Charleston, SC 29425, USA.

Bioinformatics (Oxford, England)
|February 26, 2005
PubMed
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Researchers developed a new method to represent complex biological systems, like SARS-CoV-2, using software engineering principles. This approach allows for better integration and understanding of large biological systems.

Area of Science:

  • Systems Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Studying biology at a systems level is crucial but lacks standardized methodologies for information integration.
  • A multidisciplinary approach combining computer science and biology is needed to address this gap.

Purpose of the Study:

  • To develop a consistent methodology for integrating and representing biological information at the systems level.
  • To demonstrate the application of software engineering principles in systems biology.

Main Methods:

  • Adapted a sequential software engineering process.
  • Applied the process to reverse-engineer a complex biological system: severe acquired respiratory syndrome-coronavirus (SARS-CoV) viral infection.
  • Represented the biological system as an object-oriented software system.

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Main Results:

  • Successfully reverse-engineered the SARS-CoV viral infection using software engineering techniques.
  • Developed an object-oriented software representation of the complex biological system.
  • Demonstrated the scalability of the object-oriented software engineering approach for integrating large biological systems.

Conclusions:

  • The adapted software engineering process provides a viable methodology for systems-level biological information integration.
  • Object-oriented software engineering is a scalable technology applicable to complex biological systems.
  • This approach facilitates a more comprehensive understanding of intricate biological processes.