Network diffusion on multiple-layers: current approaches and integrative analysis of Rheumatoid Arthritis data.

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1 Institute of Biomedical Technologies - CNR, Segrate (MI), Italy
2 Department of Industrial and Information Engineering, University of Pavia, Pavia, Italy
DOI
10.7287/peerj.preprints.3310v1
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
Di Nanni N, Gnocchi M, Moscatelli M, Milanesi L, Mosca E. 2017. Network diffusion on multiple-layers: current approaches and integrative analysis of Rheumatoid Arthritis data. PeerJ Preprints 5:e3310v1

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.