Metabolic networks are almost nonfractal: a comprehensive evaluation

Area of Science:

• Systems Biology
• Network Science
• Bioinformatics

Background:

• Metabolic networks are crucial for understanding cellular functions.
• Network self-similarity (fractality) has been considered a key topological property.
• Recent studies have questioned the existence of fractality in metabolic networks.

Purpose of the Study:

• To comprehensively evaluate the fractality of metabolic networks.
• To compare the topological properties of earlier and latest versions of metabolic networks.
• To investigate the reasons behind previously reported network fractality.

Main Methods:

• Utilized a box-covering method to assess network fractality.
• Analyzed both an earlier and the latest version of metabolic networks.
• Compared the self-similarity characteristics between the two network versions.

Main Results:

• The latest metabolic networks exhibit almost self-dissimilar properties.
• Earlier versions of metabolic networks demonstrated fractal characteristics.
• The observed fractality in earlier networks might be an artifact of increased network density and data incompleteness.

Conclusions:

• The fractality of metabolic networks is questionable in their latest versions.
• Previously reported fractality may stem from data limitations and network randomization.
• Further research is needed for a refined definition of network fractality and re-evaluation of self-similarity.