The aim of this study was to analyze previously published gene expression data of skeletal muscle biopsies of Duchenne muscular dystrophy (DMD) patients and controls (gene expression omnibus database, accession #GSE6011) using systems biology approaches. We applied an unsupervised method to discriminate patient and control populations, based on principal component analysis, using the gene expressions as units and patients as variables. The genes having the highest absolute scores in the discrimination between the groups, were then analyzed in terms of gene expression networks, on the basis of their mutual correlation in the two groups. The correlation network structures suggest two different modes of gene regulation in the two groups, reminiscent of important aspects of DMD pathogenesis.
|Numero di pagine||8|
|Rivista||IEEE/ACM Transactions on Computational Biology and Bioinformatics|
|Stato di pubblicazione||Pubblicato - 2013|