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Functional analysis of miRNAs using the DIANA tools online suite

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Auteur
Vlachos I.S., Hatzigeorgiou A.G.
Date
2017
Language
en
DOI
10.1007/978-1-4939-6563-2_2
Sujet
microRNA
messenger RNA
microRNA
3' untranslated region
bioinformatics
computer model
gene expression
human
next generation sequencing
nonhuman
RNA analysis
RNA sequence
algorithm
binding site
gene expression regulation
genetic database
genetics
Internet
software
Algorithms
Binding Sites
Databases, Genetic
Gene Expression Regulation
Humans
Internet
MicroRNAs
RNA, Messenger
Software
Humana Press Inc.
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Résumé
microRNAs (miRNAs) are central regulators of gene expression. They are actively studied for their involvement in numerous physiological and pathological conditions but also as diagnostic biomarkers or promising therapeutic targets. The increased complexity of the miRNA interactomes hinders straightforward interpretation of miRNA expression differences between states and conditions. To this end, functional analysis web servers process and combine experimental and in silico data, enabling researchers to uncover targeted pathways and transcriptional mechanisms that are hidden within numerous interactions and vast expression datasets. DIANA-tools (www.microrna.gr) is a web server hosting state-of-the-art utilities and databases for miRNA functional investigation. Available utilities cover a wide scope of different needs and research scenarios, rendering DIANA website a one-stop-shop for miRNA analyses. The most commonly utilized databases and algorithms include DIANA-microT-CDS, DIANA-TarBase v7.0, DIANA-lncBase v2.0, DIANA-miRGen v3.0, DIANA-miRPath v3.0, and DIANA-mirExTra v2.0. In the presented protocol, we will utilize different online tools in order to explore miRNA functions and to identify probable targets of interest for downstream analyses and wet lab experiments. The combined use of different applications from the DIANA suite can shed light to numerous different aspects of miRNA regulation and regulatory function, without the necessity for extensive bioinformatics expertise or computational infrastructure. © Springer Science+Business Media New York 2017.
URI
http://hdl.handle.net/11615/80653
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