This paper presents a top-down strategy to detect features in genomic sequences. The strategy's core is to exploit dictionary-based compression algorithms and analyse the content of the automatically generated dictionary. We classify the different over-represented segments and in the case study we correlate them to experimentally identified or theoretically forecasted biological features. A large spectrum analysis reveals that the only feature co-located with the a priori extracted segments is the torsional flexibility of DNA, while non-B DNA configurations are anti-localized and other features are mostly independent of the extracted sequences. This analysis unravels complex relationships between the linguistic structures investigated under our approach and some known biological features. (C) 2010 Elsevier Ltd. All rights reserved.
A top-down linguistic approach to the analysis of genomic sequences: The metabotropic Glutamate receptors 1 and 5 in Human and in Mouse as a case study.
SBRANA, ISABELLA;MARANGONI, ROBERTO
2011-01-01
Abstract
This paper presents a top-down strategy to detect features in genomic sequences. The strategy's core is to exploit dictionary-based compression algorithms and analyse the content of the automatically generated dictionary. We classify the different over-represented segments and in the case study we correlate them to experimentally identified or theoretically forecasted biological features. A large spectrum analysis reveals that the only feature co-located with the a priori extracted segments is the torsional flexibility of DNA, while non-B DNA configurations are anti-localized and other features are mostly independent of the extracted sequences. This analysis unravels complex relationships between the linguistic structures investigated under our approach and some known biological features. (C) 2010 Elsevier Ltd. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.