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. 2010 Oct 29;5(10):e13668.
doi: 10.1371/journal.pone.0013668.

A systems biology strategy on differential gene expression data discloses some biological features of atrial fibrillation

Federica Censi  1 , Giovanni Calcagnini, Pietro Bartolini, Alessandro Giuliani
Affiliations

A systems biology strategy on differential gene expression data discloses some biological features of atrial fibrillation

Federica Censi et al. PLoS One. .

Abstract

Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with extensive structural, contractile, and electrophysiological remodeling. In this manuscript we re-analyzed gene expression data from a microarray experiment on AF patients and control tissues, using a new paradigm based on a posteriori unsupervised strategy in which the discrimination of patients comes out from purely syntactical premises. This paradigm, more adherent to biological reality where genes work in highly connected networks, allowed us to get both a very precise patients/control discrimination and the discovery of cell adhesion/tissue modeling and inflammation processes as the main dimensions of AF.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. The graph axes are the genome-wide profiles of two samples (an AF and a control one), the vector points are the single genes.
The overwhelming order parameter correlating around 20000 genes expression values is evident. The line roughly corresponds to PC1.
Figure 2
Figure 2. Discrimination plane obtained combining FL2A and FL2B.
The points in the plot correspond to individual patients (N = normal patients; AF =  atrial fibrillation patients). The plot is spanned by the two most relevant discriminating factors obtained from the two chips. The discriminating line is the result of the application of linear discriminant analysis on the FL2A and FL2B space.
See this image and copyright information in PMC

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