The post-genomic era of biological network alignment

Area of Science:

• Bioinformatics
• Computational Biology
• Systems Biology

Background:

• Biological network alignment uncovers topological and functional similarities between molecular networks of different species.
• It complements genomic sequence alignment by enabling biological knowledge transfer from well-studied to less-studied species.
• Conserved network regions facilitate the transfer of insights into biological functions, evolution, and disease.

Purpose of the Study:

• To review the computational challenges in biological network alignment.
• To survey existing approaches for solving the network alignment problem and evaluating alignment quality.
• To discuss biomedical applications and recent innovative efforts in the field.

Main Methods:

• Review of computational challenges and existing algorithms for biological network alignment.
• Analysis of methods for evaluating the quality of network alignments.
• Exploration of biomedical applications and recent advancements.

Main Results:

• Identified key computational challenges in aligning biological networks.
• Cataloged diverse existing approaches and their evaluation metrics.
• Highlighted biomedical applications and emerging innovative strategies.

Conclusions:

• Network alignment is crucial for comparative biological research and knowledge transfer.
• Open research questions remain in comparative biological network analysis.
• Further research can deepen understanding of life, evolution, disease, and therapeutics.