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Assessment of community efforts to advance network-based prediction of protein–protein interactions
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Authors
Wang, Xu Wen
Madeddu, Lorenzo
Spirohn, Kerstin
Martini, Leonardo
Fazzone, Adriano
Becchetti, Luca
Wytock, Thomas P.
Kovács, István A.
Balogh, Olivér M.
Benczik, Bettina
Pétervári, Mátyás
Ágg, Bence
Ferdinandy, Péter
Vulliard, Loan
Menche, Jörg
Colonnese, Stefania
Petti, Manuela
Scarano, Gaetano
Cuomo, Francesca
Hao, Tong
Laval, Florent
Willems, Luc
Twizere, Jean Claude
Vidal, Marc
Calderwood, Michael A.
Petrillo, Enrico
Barabási, Albert László
Silverman, Edwin K.
Loscalzo, Joseph
Velardi, Paola
Liu, Yang Yu
Madeddu, Lorenzo
Spirohn, Kerstin
Martini, Leonardo
Fazzone, Adriano
Becchetti, Luca
Wytock, Thomas P.
Kovács, István A.
Balogh, Olivér M.
Benczik, Bettina
Pétervári, Mátyás
Ágg, Bence
Ferdinandy, Péter
Vulliard, Loan
Menche, Jörg
Colonnese, Stefania
Petti, Manuela
Scarano, Gaetano
Cuomo, Francesca
Hao, Tong
Laval, Florent
Willems, Luc
Twizere, Jean Claude
Vidal, Marc
Calderwood, Michael A.
Petrillo, Enrico
Barabási, Albert László
Silverman, Edwin K.
Loscalzo, Joseph
Velardi, Paola
Liu, Yang Yu
Editors
Keywords
General Chemistry
General Biochemistry,Genetics and Molecular Biology
General Physics and Astronomy
SDG 3 - Good Health and Well-being
General Biochemistry,Genetics and Molecular Biology
General Physics and Astronomy
SDG 3 - Good Health and Well-being
URI
https://hdl.handle.net/20.500.14018/27125
Abstract
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.
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Publisher
Place of Publication
Type
Journal article
Date
2023-03-22
Language
ISBN
Identifiers
10.1038/s41467-023-37079-7