Analysis of miRNA expression profiles in breast cancer using biclustering

BMC Bioinformatics
Antonino FiannacaAlfonso Urso

Abstract

MicroRNAs (miRNAs) are important key regulators in multiple cellular functions, due to their a crucial role in different physiological processes. MiRNAs are differentially expressed in specific tissues, during specific cell status, or in different diseases as tumours. RNA sequencing (RNA-seq) is a Next Generation Sequencing (NGS) method for the analysis of differential gene expression. Using machine learning algorithms, it is possible to improve the functional significance interpretation of miRNA in the analysis and interpretation of data from RNA-seq. Furthermore, we tried to identify some patterns of deregulated miRNA in human breast cancer (BC), in order to give a contribution in the understanding of this type of cancer at the molecular level. We adopted a biclustering approach, using the Iterative Signature Algorithm (ISA) algorithm, in order to evaluate miRNA deregulation in the context of miRNA abundance and tissue heterogeneity. These are important elements to identify miRNAs that would be useful as prognostic and diagnostic markers. Considering a real word breast cancer dataset, the evaluation of miRNA differential expressions in tumours versus healthy tissues evidenced 12 different miRNA clusters, associated to specifi...Continue Reading

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Citations

Aug 25, 2016·Biochimica Et Biophysica Acta·Yao-Fei PeiXi-Qiang Liu
Nov 16, 2017·BMC Bioinformatics·Liying YangJianhua Wei
Jan 13, 2017·Briefings in Bioinformatics·Sipko van DamJoão Pedro de Magalhães
Dec 1, 2018·BMC Bioinformatics·Antonino FiannacaAlfonso Urso
Feb 12, 2017·BMC Bioinformatics·Antonino FiannacaAlfonso Urso
Sep 26, 2020·Scientific Reports·Hamid R EghbalniaPiotr Chomczynski
Apr 12, 2021·Medical & Biological Engineering & Computing·Koyel MandalBhogeswar Borah

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Datasets Mentioned

BETA
GSE28884

Methods Mentioned

BETA
RNA-seq
ISA

Software Mentioned

UCSC Genome browser
MLR
ISA
MetaMirClust
SAMBA
R package isa2

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