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Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
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BEL2ABM: agent-based simulation of static models in Biological Expression Language.

Michaela Gündel1,2, Charles Tapley Hoyt1,2, Martin Hofmann-Apitius1,2

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BEL2ABM software generates dynamic agent-based models from static Biological Expression Language templates, enabling temporal analysis of mechanistic hypotheses. This advances computational biology by adding a crucial dynamic element to knowledge assembly.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Biological Expression Language (BEL) models enable mechanistic hypothesis generation.
  • Current BEL models are static and lack temporal dynamics.
  • There is a need for dynamic modeling in biological systems analysis.

Purpose of the Study:

  • Introduce BEL2ABM, a novel software tool.
  • Enable the creation of continuous, dynamic, and executable agent-based models (ABMs) from BEL templates.
  • Overcome the limitations of static models in capturing biological temporality.

Main Methods:

  • Developed BEL2ABM using Java and NetLogo.
  • The software translates BEL graph structures into agent-based model rules.
  • Agent-based models are executable and simulate dynamic biological processes.

Main Results:

  • BEL2ABM successfully generates dynamic ABMs from BEL templates.
  • The generated models capture temporal aspects of biological mechanisms.
  • Demonstrates a method for dynamic simulation of knowledge assembly.

Conclusions:

  • BEL2ABM enhances mechanistic hypothesis generation by incorporating temporality.
  • The software provides a valuable tool for dynamic systems biology research.
  • Facilitates the transition from static knowledge representation to dynamic simulation.