Characterization and comparison of gene-centered human interactomes.

Area of Science:

• Biochemistry
• Systems Biology
• Bioinformatics

Background:

• The cellular macromolecular interaction network, or interactome, is fundamental to biological studies.
• Current human interactome maps, generated through diverse experimental and computational methods, lack consensus on their structural representation.
• Enrichment of interactome maps using literature mining and various database combinations further complicates direct comparisons.

Purpose of the Study:

• To systematically compare multiple human interactome maps.
• To assess the similarity and differences in topological properties, protein complexes, and pathway associations.
• To provide quantitative parameters and guidelines for selecting appropriate interactomes in network biology applications.

Main Methods:

• Comparative analysis of a comprehensive list of human interactomes.
• Evaluation based on network topology, protein complex identification, and molecular pathway enrichment.
• Assessment of pathway cross-talk and disease gene prediction capabilities.
• Utilizing literature-mining derived interactomes and various source databases.

Main Results:

• Significant heterogeneity exists among different human interactome maps.
• Variations were observed in topological features, identified protein complexes, and pathway representations.
• The study provides a quantitative assessment of the state-of-the-art in human interactome mapping.

Conclusions:

• No single human interactome map is universally superior; selection depends on the specific network biology application.
• Guidelines are provided for researchers to choose the most suitable interactome datasets.
• This work clarifies the landscape of human interactome data and aids in future research directions.