Network diffusion on multiple-layers: current approaches and integrative analysis of Rheumatoid Arthritis data.
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology, Genomics
- Keywords
- Rheumatoid Arthritis, Network diffusion, multiple omics data
- Copyright
- © 2017 Di Nanni et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. Network diffusion on multiple-layers: current approaches and integrative analysis of Rheumatoid Arthritis data. PeerJ Preprints 5:e3310v1 https://doi.org/10.7287/peerj.preprints.3310v1
Abstract
Network Diffusion has been proposed in several applications, thanks to its ability of amplifying biological signals and prioritizing genes that may be associated with a disease. Not surprising, the success of Network Diffusion on a “single layer” led to the first approaches for the joint analysis of multi-omics data.
Here, we review integrative methods based on Network Diffusion that have been proposed with several aims (e.g. patient stratification, module detection, function prediction). We used Network Diffusion to analyse, in the context of physical and functional protein-protein interactions, genetic variation, DNA methylation and gene expression data from a study on Rheumatoid Arthritis. We identified functionally related genes with multiple alterations.
Author Comment
This is an abstract which has been accepted for the NETTAB 2017 Workshop.