Combing the Hairball: Improving Visualization of miRNA-Target Interaction Networks

Francesco Russo; Jessica Xin Hu; Jose Alejandro Romero Herrera; Søren Brunak

doi:10.1007/978-1-4939-9207-2_15

Combing the Hairball: Improving Visualization of miRNA-Target Interaction Networks

Francesco Russo, Jessica Xin Hu, Jose Alejandro Romero Herrera, Søren Brunak

Disease Systems Biology Program

Abstract

The visualization of regulatory networks is becoming increasingly important in order to understand molecular mechanisms and diseases. MicroRNAs (miRNAs) are small noncoding RNAs (ncRNAs) responsible of the post-transcriptional regulation of messenger RNAs (mRNAs) and other ncRNAs. MiRNAs are involved in numerous biological processes including development, cell proliferation, and apoptosis. They are also key molecules in major complex diseases such as cancer and cardiovascular diseases. A single miRNA can regulate many targets, making the analysis and visualization of these complex networks challenging. Here, we present standard and advanced visualization approaches to represent networks with a special focus on miRNA-target interactions.

Originalsprog	Engelsk
Titel	MicroRNA Target Identification : Methods and Protocols
Redaktører	Alessandro Laganà
Antal sider	11
Forlag	Humana Press
Publikationsdato	2019
Sider	279-289
ISBN (Trykt)	978-1-4939-9206-5
ISBN (Elektronisk)	978-1-4939-9207-2
DOI	https://doi.org/10.1007/978-1-4939-9207-2_15
Status	Udgivet - 2019

Navn	Methods in Molecular Biology
Vol/bind	1970
ISSN	1064-3745

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10.1007/978-1-4939-9207-2_15

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Combing the Hairball: Improving Visualization of miRNA-Target Interaction Networks. / Russo, Francesco ; Hu, Jessica Xin ; Romero Herrera, Jose Alejandro et al.
MicroRNA Target Identification: Methods and Protocols. red. / Alessandro Laganà. Humana Press, 2019. s. 279-289 (Methods in Molecular Biology, Bind 1970).

Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › peer review

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Combing the Hairball: Improving Visualization of miRNA-Target Interaction Networks

Abstract

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