Title: A Data Mining Library for mi RNA Annotation and Analysis
Authors: Nuzzo, Angelo
Beretta, Riccardo
Mulas, Francesca
Roobrouck VD, Valerie
Verfaillie, Catherine
Zupan, Blaz
Bellazzi, Riccardo
Issue Date: 2011
Publisher: Springer-Verlag
Host Document: 13th Conference on Artificial Intelligence in Medicine, AIME 2011, Bled, Slovenia, July 2-6, 2011. Proceedings vol:2 pages:80-84
Series Title: Lecture Notes in Computer Science
Conference: AIME 2011 location:Bled, Slovenia date:July 2-6
Abstract: Understanding the key role that miRNAs play in the regulation of gene expression is one of the most important challenges in modern molecular biology. Standard gene set enrichment analysis (GSEA) is not appropriate in this context, due to the low specificity of the relation between miRNAs and their target genes. We developed alternative strategies to gain better insights in the differences in biological processes involved in different experimental conditions. We here describe a novel method to analyze and interpret miRNA expression data correctly, and demonstrate that annotating miRNA directly to biological processes through their target genes (which is nevertheless the only way possible) is a non-trivial task. We are currently employing the same strategy to relate miRNA expression patterns directly to pathway information, to generate new hypotheses, which may be relevant for the interpretation of their role in the gene expression regulatory processes.
ISBN: 978-3-642-22217-7
Publication status: published
KU Leuven publication type: IMa
Appears in Collections:Stem Cell Biology and Embryology (+)

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