Advancing Network Biology with FunCoup 6

The FunCoup network database (https://funcoup.org) provides comprehensive functional association networks of genes/proteins that were inferred by integrating massive amounts of multi-omics data, combined with orthology transfer. We recently released FunCoup 6, a major update, providing researchers with a significantly improved and redesigned platform for exploring the functional coupling interactome. The new release includes networks for 23 primary species and 618 additional orthology-transferred species.The FunCoup networks can be used for a variety of purposes. The website allows users to visualize tissue-specific networks and regulatory interactions. A unique feature of theFunCoup website is the possibility to perform ‘comparative interactomics’ such that subnetworks of different species are aligned with each other using orthologs. This way the level of conservation of the network between species can be easily studied.

Key innovations in release 6 include:

• Enhanced regulatory link coverage: FunCoup 6 now includes over half a million directed gene regulatory links in the human network alone, offering deeper insights into transcriptional regulation. 13 species in FunCoup now contain regulatory links, comprising~1 M links in total.
• New website: We completely redesigned the FunCoup website and updated its API functionalities, enhancing user accessibility and experience.
• New training framework: We developed a bin-free Bayesian training method that improves the accuracy and reproducibility of link prediction.
• Integrated advanced online tools for network analysis: The integration of TOPAS for disease and drug target module identification, along with network-based KEGG pathway enrichment analysis using ANUBIX, expands the utility of FunCoup 6 for biomedical research. For enhanced visualization of the ANUBIX results, FunCoup links to the PathBIX(https://pathbix.sbc.su.se/) web server, where all details of the crosstalk to a pathway is shown.

Another integrated online tool is MaxLink, for network-based gene prioritization that identifies and ranks genes that have a statistically significant level of links to the query list. This functionality can be used e.g. to predict new potential disease genes from an initial set of genes with known association to a disease.We further used FunCoup to evaluate network crosstalk-based methods that perform well for pathway enrichment in their ability to predict drug repurposing. The network crosstalk-based methods ANUBIX, BinoX, and NEAT were compared to a state-of-the-art technique, NetworkProximity. We found that network crosstalk-based drug repurposing is able to rival the state-of-the-art method.