Recent advances in modeling languages for pathway maps and computable biological networks.

Area of Science:

• Systems biology
• Computational biology
• Bioinformatics

Background:

• Systems biology models are increasing in complexity.
• Existing modeling languages may lack the expressivity for sophisticated annotation, simulation, and analysis.
• Effective model sharing and collaboration require uniform data structures and language standards.

Purpose of the Study:

• To review recent advancements in systems biology modeling languages.
• To examine the capabilities of BEL, PySB, and BCML in meeting the demands of complex biological modeling.
• To assess how these languages facilitate high-resolution annotation, simulation, analysis, and collaboration.

Main Methods:

• Brief review of three emerging systems biology modeling languages: BEL, PySB, and BCML.
• Analysis of language features supporting model representation, annotation, simulation, and analysis.
• Evaluation of their adherence to standards for data sharing and collaboration.

Main Results:

• BEL, PySB, and BCML offer increased expressivity and flexibility for complex systems biology models.
• These languages provide features for high-resolution annotation and sophisticated simulation/analysis.
• They incorporate uniform data structures (e.g., graphs) to facilitate model sharing and collaboration.

Conclusions:

• Recent systems biology modeling languages are evolving to meet the challenges of complex data.
• BEL, PySB, and BCML represent significant steps towards standardized, collaborative, and analytically powerful biological modeling.
• These languages are crucial for researchers to effectively manage and interpret complex biological systems data.