Cargando…
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...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057719/ https://www.ncbi.nlm.nih.gov/pubmed/32180795 http://dx.doi.org/10.3389/fgene.2020.00106 |
_version_ | 1783503723141529600 |
---|---|
author | Di Nanni, Noemi Bersanelli, Matteo Milanesi, Luciano Mosca, Ettore |
author_facet | Di Nanni, Noemi Bersanelli, Matteo Milanesi, Luciano Mosca, Ettore |
author_sort | Di Nanni, Noemi |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-7057719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70577192020-03-16 Network Diffusion Promotes the Integrative Analysis of Multiple Omics Di Nanni, Noemi Bersanelli, Matteo Milanesi, Luciano Mosca, Ettore Front Genet Genetics 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. Frontiers Media S.A. 2020-02-27 /pmc/articles/PMC7057719/ /pubmed/32180795 http://dx.doi.org/10.3389/fgene.2020.00106 Text en Copyright © 2020 Di Nanni, Bersanelli, Milanesi and Mosca http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Di Nanni, Noemi Bersanelli, Matteo Milanesi, Luciano Mosca, Ettore Network Diffusion Promotes the Integrative Analysis of Multiple Omics |
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 | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057719/ https://www.ncbi.nlm.nih.gov/pubmed/32180795 http://dx.doi.org/10.3389/fgene.2020.00106 |
work_keys_str_mv | AT dinanninoemi networkdiffusionpromotestheintegrativeanalysisofmultipleomics AT bersanellimatteo networkdiffusionpromotestheintegrativeanalysisofmultipleomics AT milanesiluciano networkdiffusionpromotestheintegrativeanalysisofmultipleomics AT moscaettore networkdiffusionpromotestheintegrativeanalysisofmultipleomics |