Identification of Disease-miRNA Networks Across Different Cancer Types Using SWIM.
Cancer
MicroRNA
Network biology
Switch genes
TCGA
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
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