Assessment of community efforts to advance network-based prediction of protein–protein interactions

Xu Wen Wang, Lorenzo Madeddu, Kerstin Spirohn, Leonardo Martini, Adriano Fazzone, Luca Becchetti, Thomas P. Wytock, István A. Kovács, Olivér M. Balogh, Bettina Benczik, Mátyás Pétervári, Bence Ágg, Péter Ferdinandy, Loan Vulliard, Jörg Menche, Stefania Colonnese, Manuela Petti, Gaetano Scarano, Francesca Cuomo, Tong HaoFlorent Laval, Luc Willems, Jean Claude Twizere, Marc Vidal, Michael A. Calderwood, Enrico Petrillo, Albert László Barabási, Edwin K. Silverman, Joseph Loscalzo, Paola Velardi*, Yang Yu Liu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Comprehensive understanding of the human protein-protein interaction (PPI) network, aka the human interactome, can provide important insights into the molecular mechanisms of complex biological processes and diseases. Despite the remarkable experimental efforts undertaken to date to determine the structure of the human interactome, many PPIs remain unmapped. Computational approaches, especially network-based methods, can facilitate the identification of previously uncharacterized PPIs. Many such methods have been proposed. Yet, a systematic evaluation of existing network-based methods in predicting PPIs is still lacking. Here, we report community efforts initiated by the International Network Medicine Consortium to benchmark the ability of 26 representative network-based methods to predict PPIs across six different interactomes of four different organisms: A. thaliana, C. elegans, S. cerevisiae, and H. sapiens. Through extensive computational and experimental validations, we found that advanced similarity-based methods, which leverage the underlying network characteristics of PPIs, show superior performance over other general link prediction methods in the interactomes we considered.

Original languageEnglish (US)
Article number1582
JournalNature communications
Issue number1
StatePublished - Dec 2023

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)


Dive into the research topics of 'Assessment of community efforts to advance network-based prediction of protein–protein interactions'. Together they form a unique fingerprint.

Cite this