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Assessment of community efforts to advance network-based prediction of protein-protein interactions.
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.
Afiliación
  • Wang XW; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
  • Madeddu L; Translational and Precision Medicine Department Sapienza University of Rome, Rome, Italy.
  • Spirohn K; Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
  • Martini L; Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA.
  • Fazzone A; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
  • Becchetti L; Department of Computer, Control, and Management Engineering "Antonio Rubert", Sapienza University of Rome, Rome, Italy.
  • Wytock TP; CENTAI Institute, Turin, Italy.
  • Kovács IA; Department of Computer, Control, and Management Engineering "Antonio Rubert", Sapienza University of Rome, Rome, Italy.
  • Balogh OM; Department of Physics and Astronomy, Northwestern University, Evanston, IL, 60208, USA.
  • Benczik B; Department of Physics and Astronomy, Northwestern University, Evanston, IL, 60208, USA.
  • Pétervári M; Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL, 60208, USA.
  • Ágg B; Cardiometabolic and MTA-SE System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
  • Ferdinandy P; Cardiometabolic and MTA-SE System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
  • Vulliard L; Pharmahungary Group, 6722, Szeged, Hungary.
  • Menche J; Cardiometabolic and MTA-SE System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
  • Colonnese S; Cardiometabolic and MTA-SE System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
  • Petti M; Pharmahungary Group, 6722, Szeged, Hungary.
  • Scarano G; Cardiometabolic and MTA-SE System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
  • Cuomo F; Pharmahungary Group, 6722, Szeged, Hungary.
  • Hao T; CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
  • Laval F; Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria.
  • Willems L; CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
  • Twizere JC; Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria.
  • Vidal M; Faculty of Mathematics, University of Vienna, Vienna, Austria.
  • Calderwood MA; Department of Information Engineering, Electronics, and Telecommunications (DIET), University of Rome "Sapienza", Rome, Italy.
  • Petrillo E; Department of Computer, Control, and Management Engineering "Antonio Rubert", Sapienza University of Rome, Rome, Italy.
  • Barabási AL; Department of Information Engineering, Electronics, and Telecommunications (DIET), University of Rome "Sapienza", Rome, Italy.
  • Silverman EK; Department of Information Engineering, Electronics, and Telecommunications (DIET), University of Rome "Sapienza", Rome, Italy.
  • Loscalzo J; Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
  • Velardi P; Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA.
  • Liu YY; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
Nat Commun ; 14(1): 1582, 2023 03 22.
Article en En | MEDLINE | ID: mdl-36949045
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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Mapeo de Interacción de Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Mapeo de Interacción de Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido