Identification of Disease-miRNA Networks Across Different Cancer Types Using SWIM.


Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2019
Historique:
entrez: 10 4 2019
pubmed: 10 4 2019
medline: 7 9 2019
Statut: ppublish

Résumé

MicroRNAs (miRNAs) are small noncoding RNAs (ncRNAs) involved in several biological processes and diseases. MiRNAs regulate gene expression at the posttranscriptional level, mostly downregulating their targets by binding specific regions of transcripts through imperfect sequence complementarity. Prediction of miRNA-binding sites is challenging, and target prediction algorithms are usually based on sequence complementarity. In the last years, it has been shown that by adding miRNA and protein coding gene expression, we are able to build tissue-, cell line-, or disease-specific networks improving our understanding of complex biological scenarios. In this chapter, we present an application of a recently published software named SWIM, that allows to identify key genes in a network of interactions by defining appropriate "roles" of genes according to their local/global positioning in the overall network. Furthermore, we show how the SWIM software can be used to build miRNA-disease networks, by applying the approach to tumor data obtained from The Cancer Genome Atlas (TCGA).

Identifiants

pubmed: 30963493
doi: 10.1007/978-1-4939-9207-2_10
doi:

Substances chimiques

Biomarkers, Tumor 0
MicroRNAs 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

169-181

Auteurs

Giulia Fiscon (G)

Institute for Systems Analysis and Computer Science Antonio Ruberti, National Research Council, Rome, Italy.
SysBio Centre for Systems Biology, Milan, Italy.

Federica Conte (F)

Institute for Systems Analysis and Computer Science Antonio Ruberti, National Research Council, Rome, Italy.
SysBio Centre for Systems Biology, Milan, Italy.

Lorenzo Farina (L)

Department of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza University of Rome, Rome, Italy.

Marco Pellegrini (M)

Institute of Informatics and Telematics, National Research Council, Pisa, Italy.

Francesco Russo (F)

Faculty of Health and Medical Sciences¸ Novo Nordisk Foundation Center for Protein Research, Translational Disease Systems Biology, University of Copenhagen, Copenhagen, Denmark. francesco.russo@cpr.ku.dk.

Paola Paci (P)

Institute for Systems Analysis and Computer Science Antonio Ruberti, National Research Council, Rome, Italy. paola.paci@iasi.cnr.it.
SysBio Centre for Systems Biology, Milan, Italy. paola.paci@iasi.cnr.it.

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