Context analysis in microRNA data: A Rosetta Stone approach

Authors:
Stefano Rovetta;Francesco Masulli;Maura Edelweiss Monville;Giuseppe Russo
Affiliations:
Department of Computer and Information Sciences, University of Genova, Via Dodecaneso 35, 16146 Genova, Italy;Department of Computer and Information Sciences, University of Genova, Via Dodecaneso 35, 16146 Genova, Italy and Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnol ...;Department of Computer and Information Sciences, University of Genova, Via Dodecaneso 35, 16146 Genova, Italy;Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, Temple University, BioLife Science Bldg., 1900 N 12th Street, Philadelphia, PA 19122 USA
Venue:
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
Year:
2011

Citing 3
Cited 0

A vector space model for automatic indexing

Communications of the ACM
GNU Scientific Library Reference Manual - Third Edition

GNU Scientific Library Reference Manual - Third Edition
Searching for microRNA prostate cancer target genes

IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

MicroRNAs are a hot topic of research in molecular biology. Their role is however still to be elucidated in full. We present a data-oriented approach to the study of microRNA-gene interactions, building heavily on methods of document analysis. The paper aims at illustrating an approach rather than specific methods of analysis, however some sample results are also presented, which show how latent information can be exploited to suggest directions for laboratory experiments, thus avoiding unnecessary expense in time and resources.