An Association Rule Mining Approach to Discover lncRNAs Expression Patterns in Cancer Datasets
Joint Authors
Cremaschi, Paolo
Carriero, Roberta
Astrologo, Stefania
Colì, Caterina
Lisa, Antonella
Parolo, Silvia
Bione, Silvia
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-07-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
In the past few years, the role of long noncoding RNAs (lncRNAs) in tumor development and progression has been disclosed although their mechanisms of action remain to be elucidated.
An important contribution to the comprehension of lncRNAs biology in cancer could be obtained through the integrated analysis of multiple expression datasets.
However, the growing availability of public datasets requires new data mining techniques to integrate and describe relationship among data.
In this perspective, we explored the powerness of the Association Rule Mining (ARM) approach in gene expression data analysis.
By the ARM method, we performed a meta-analysis of cancer-related microarray data which allowed us to identify and characterize a set of ten lncRNAs simultaneously altered in different brain tumor datasets.
The expression profiles of the ten lncRNAs appeared to be sufficient to distinguish between cancer and normal tissues.
A further characterization of this lncRNAs signature through a comodulation expression analysis suggested that biological processes specific of the nervous system could be compromised.
American Psychological Association (APA)
Cremaschi, Paolo& Carriero, Roberta& Astrologo, Stefania& Colì, Caterina& Lisa, Antonella& Parolo, Silvia…[et al.]. 2015. An Association Rule Mining Approach to Discover lncRNAs Expression Patterns in Cancer Datasets. BioMed Research International،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1054359
Modern Language Association (MLA)
Cremaschi, Paolo…[et al.]. An Association Rule Mining Approach to Discover lncRNAs Expression Patterns in Cancer Datasets. BioMed Research International No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1054359
American Medical Association (AMA)
Cremaschi, Paolo& Carriero, Roberta& Astrologo, Stefania& Colì, Caterina& Lisa, Antonella& Parolo, Silvia…[et al.]. An Association Rule Mining Approach to Discover lncRNAs Expression Patterns in Cancer Datasets. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1054359
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1054359