ArticleBMC bioinformatics2015
Analysis of miRNA expression profiles in breast cancer using biclustering.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 45 citations in OpenAlex.
- miR-6087 Might Regulate Cell Cycle-Related mRNAs During Cardiomyogenesis of hESCs.Bioinformatics and biology insights · 2023Article
- Rank-preserving biclustering algorithm: a case study on miRNA breast cancer.Medical & biological engineering & computing · 2021Article
- miR-21 Induces Chemoresistance in Ovarian Cancer Cells via Mediating the Expression and Interaction of CD44v6 and P-gp.OncoTargets and therapy · 2021Article
- Research hotspots and trends analysis of ankylosing spondylitis: a bibliometric and scientometric analysis from 2009 to 2018.Annals of translational medicine · 2020Article
- microRNA Expression Profile in Single Hormone Receptor-Positive Breast Cancers is Mainly Dependent on HER2 Status-A Pilot Study.Diagnostics (Basel, Switzerland) · 2020Article
- Downregulation of microRNA-1246 inhibits tumor growth and promotes apoptosis of cervical cancer cells by targeting thrombospondin-2.Oncology letters · 2019Article
- A rectified factor network based biclustering method for detecting cancer-related coding genes and miRNAs, and their interactions.Methods (San Diego, Calif.) · 2019Article
- It is time to apply biclustering: a comprehensive review of biclustering applications in biological and biomedical data.Briefings in bioinformatics · 2019Review
- Development of a Fully Cross-Validated Bayesian Network Approach for Local Control Prediction in Lung Cancer.IEEE transactions on radiation and plasma medical sciences · 2019Article
- Article
- miRTissue: a web application for the analysis of miRNA-target interactions in human tissues.BMC bioinformatics · 2018Article
- BioGraph: a web application and a graph database for querying and analyzing bioinformatics resources.BMC systems biology · 2018Article
- Gene co-expression analysis for functional classification and gene-disease predictions.Briefings in bioinformatics · 2018Article
- Promotional effect of microRNA-194 on breast cancer cells via targeting F-box/WD repeat-containing protein 7.Oncology letters · 2018Article
- Analysis of breast cancer subtypes by AP-ISA biclustering.BMC bioinformatics · 2017Article
- MiRNATIP: a SOM-based miRNA-target interactions predictor.BMC bioinformatics · 2016Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMicroRNAs (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.
resultsWe 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 specific groups of patients. The identified miRNAs were deregulated in breast tumours compared to healthy controls. Our approach has shown the association between specific sub-class of tumour samples having the same immuno-histo-chemical and/or histological features. Biclusters have been validated by means of two online repositories, MetaMirClust database and UCSC Genome Browser, and using another biclustering algorithm.
conclusionsThe obtained results with biclustering algorithm aimed first of all to give a contribute in the differential expression analysis in a cohort of BC patients and secondly to support the potential role that these non-coding RNA molecules could play in the clinical practice, in terms of prognosis, evolution of tumour and treatment response.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.