Network Diffusion Promotes the Integrative Analysis of Multiple Omics
The development of integrative methods is one of the main challenges in bioinformatics. Network-based methods for the analysis of multiple gene-centered datasets take into account known and/or inferred relations between genes. In the last decades, the mathematical machinery of network diffusion—also...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-02-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2020.00106/full |
| _version_ | 1818614064462430208 |
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| author | Noemi Di Nanni Noemi Di Nanni Matteo Bersanelli Matteo Bersanelli Luciano Milanesi Ettore Mosca |
| author_facet | Noemi Di Nanni Noemi Di Nanni Matteo Bersanelli Matteo Bersanelli Luciano Milanesi Ettore Mosca |
| author_sort | Noemi Di Nanni |
| collection | DOAJ |
| description | The development of integrative methods is one of the main challenges in bioinformatics. Network-based methods for the analysis of multiple gene-centered datasets take into account known and/or inferred relations between genes. In the last decades, the mathematical machinery of network diffusion—also referred to as network propagation—has been exploited in several network-based pipelines, thanks to its ability of amplifying association between genes that lie in network proximity. Indeed, network diffusion provides a quantitative estimation of network proximity between genes associated with one or more different data types, from simple binary vectors to real vectors. Therefore, this powerful data transformation method has also been increasingly used in integrative analyses of multiple collections of biological scores and/or one or more interaction networks. We present an overview of the state of the art of bioinformatics pipelines that use network diffusion processes for the integrative analysis of omics data. We discuss the fundamental ways in which network diffusion is exploited, open issues and potential developments in the field. Current trends suggest that network diffusion is a tool of broad utility in omics data analysis. It is reasonable to think that it will continue to be used and further refined as new data types arise (e.g. single cell datasets) and the identification of system-level patterns will be considered more and more important in omics data analysis. |
| first_indexed | 2024-12-16T16:12:04Z |
| format | Article |
| id | doaj.art-44230144c9494c159a4a85d24ac22ebe |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-16T16:12:04Z |
| publishDate | 2020-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-44230144c9494c159a4a85d24ac22ebe2022-12-21T22:25:12ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-02-011110.3389/fgene.2020.00106488641Network Diffusion Promotes the Integrative Analysis of Multiple OmicsNoemi Di Nanni0Noemi Di Nanni1Matteo Bersanelli2Matteo Bersanelli3Luciano Milanesi4Ettore Mosca5Institute of Biomedical Technologies, National Research Council, Milan, ItalyDepartment of Industrial and Information Engineering, University of Pavia, Pavia, ItalyDepartment of Physics and Astronomy, University of Bologna, Bologna, ItalyNational Institute of Nuclear Physics (INFN), Bologna, ItalyInstitute of Biomedical Technologies, National Research Council, Milan, ItalyInstitute of Biomedical Technologies, National Research Council, Milan, ItalyThe development of integrative methods is one of the main challenges in bioinformatics. Network-based methods for the analysis of multiple gene-centered datasets take into account known and/or inferred relations between genes. In the last decades, the mathematical machinery of network diffusion—also referred to as network propagation—has been exploited in several network-based pipelines, thanks to its ability of amplifying association between genes that lie in network proximity. Indeed, network diffusion provides a quantitative estimation of network proximity between genes associated with one or more different data types, from simple binary vectors to real vectors. Therefore, this powerful data transformation method has also been increasingly used in integrative analyses of multiple collections of biological scores and/or one or more interaction networks. We present an overview of the state of the art of bioinformatics pipelines that use network diffusion processes for the integrative analysis of omics data. We discuss the fundamental ways in which network diffusion is exploited, open issues and potential developments in the field. Current trends suggest that network diffusion is a tool of broad utility in omics data analysis. It is reasonable to think that it will continue to be used and further refined as new data types arise (e.g. single cell datasets) and the identification of system-level patterns will be considered more and more important in omics data analysis.https://www.frontiersin.org/article/10.3389/fgene.2020.00106/fullintegrative analysisomics databiological networksprecision medicinenetwork-diffusion |
| spellingShingle | Noemi Di Nanni Noemi Di Nanni Matteo Bersanelli Matteo Bersanelli Luciano Milanesi Ettore Mosca Network Diffusion Promotes the Integrative Analysis of Multiple Omics Frontiers in Genetics integrative analysis omics data biological networks precision medicine network-diffusion |
| title | Network Diffusion Promotes the Integrative Analysis of Multiple Omics |
| title_full | Network Diffusion Promotes the Integrative Analysis of Multiple Omics |
| title_fullStr | Network Diffusion Promotes the Integrative Analysis of Multiple Omics |
| title_full_unstemmed | Network Diffusion Promotes the Integrative Analysis of Multiple Omics |
| title_short | Network Diffusion Promotes the Integrative Analysis of Multiple Omics |
| title_sort | network diffusion promotes the integrative analysis of multiple omics |
| topic | integrative analysis omics data biological networks precision medicine network-diffusion |
| url | https://www.frontiersin.org/article/10.3389/fgene.2020.00106/full |
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