Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein–protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Translational Medicine Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.

Molecular networks in Network Medicine: Development and applications / Silverman, E. K.; Schmidt, H. H. H. W.; Anastasiadou, E.; Altucci, L.; Angelini, M.; Badimon, L.; Balligand, J. -L.; Benincasa, G.; Capasso, G.; Conte, F.; Di Costanzo, A.; Farina, L.; Fiscon, G.; Gatto, L.; Gentili, M.; Loscalzo, J.; Marchese, C.; Napoli, C.; Paci, P.; Petti, M.; Quackenbush, J.; Tieri, P.; Viggiano, D.; Vilahur, G.; Glass, K.; Baumbach, J.. - In: WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE. - ISSN 1939-5094. - (2020). [10.1002/wsbm.1489]

Molecular networks in Network Medicine: Development and applications

Anastasiadou E.;Angelini M.;Conte F.;Farina L.;Fiscon G.;Gentili M.;Marchese C.;Paci P.;Petti M.;
2020

Abstract

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein–protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Translational Medicine Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.
2020
big data; molecular networks; network medicine
01 Pubblicazione su rivista::01g Articolo di rassegna (Review)
Molecular networks in Network Medicine: Development and applications / Silverman, E. K.; Schmidt, H. H. H. W.; Anastasiadou, E.; Altucci, L.; Angelini, M.; Badimon, L.; Balligand, J. -L.; Benincasa, G.; Capasso, G.; Conte, F.; Di Costanzo, A.; Farina, L.; Fiscon, G.; Gatto, L.; Gentili, M.; Loscalzo, J.; Marchese, C.; Napoli, C.; Paci, P.; Petti, M.; Quackenbush, J.; Tieri, P.; Viggiano, D.; Vilahur, G.; Glass, K.; Baumbach, J.. - In: WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE. - ISSN 1939-5094. - (2020). [10.1002/wsbm.1489]
File allegati a questo prodotto
File Dimensione Formato  
Silverman_Molecular_2020.pdf

solo gestori archivio

Note: Article in press
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 6.58 MB
Formato Adobe PDF
6.58 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1390780
Citazioni
  • ???jsp.display-item.citation.pmc??? 64
  • Scopus 123
  • ???jsp.display-item.citation.isi??? 110
social impact