Prolinks: a database of protein functional linkages derived from coevolution.

Area of Science:

• Genomics
• Proteomics
• Bioinformatics

Background:

• Whole-genome sequencing advances have enabled computational inference of protein function and interactions.
• Existing methods for predicting protein linkages include phylogenetic profiling, Rosetta Stone, gene neighbor, and gene cluster analyses.

Purpose of the Study:

• To integrate multiple protein linkage prediction algorithms into a unified database.
• To develop a tool for interactive visualization and exploration of predicted protein linkage networks.

Main Methods:

• Combined four established algorithms: phylogenetic profile, Rosetta Stone, gene neighbor, and gene cluster.
• Created the Prolinks database, encompassing 83 organisms and approximately 10 million high-confidence protein links.
• Developed the Proteome Navigator tool for interactive browsing of predicted linkage networks with integrated public database annotations.

Main Results:

• Established Prolinks, a large-scale database of predicted protein-protein linkages.
• Generated over 10 million high-confidence links spanning 83 diverse organisms.
• The Proteome Navigator provides an interactive platform for visualizing and analyzing these complex protein networks.

Conclusions:

• The integrated approach in Prolinks offers a robust resource for studying protein interactions.
• The Proteome Navigator facilitates accessible exploration of predicted proteome-wide linkage networks.
• This resource aids in understanding protein function and biological pathways across various species.