Application of an Integrative Computational Framework in Trancriptomic Data of Atherosclerotic Mice Suggests Numerous Molecular PlayersReportar como inadecuado

Application of an Integrative Computational Framework in Trancriptomic Data of Atherosclerotic Mice Suggests Numerous Molecular Players - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Advances in BioinformaticsVolume 2012 2012, Article ID 453513, 9 pages

Research Article

Metabolic Engineering and Bioinformatics Program, Institute of Biological Research and Biotechnology, National Hellenic Research Foundation, 48 Vas. Constantinou Avenue, 11635 Athens, Greece

Division of Clinical Medicine, School of Health and Medical Sciences, Örebro University, Örebro SE-701 82, Sweden

Biotechnology Laboratory, School of Chemical Engineering, Zografou Campus, National Technical University of Athens, 15780 Athens, Greece

Received 25 May 2012; Accepted 21 September 2012

Academic Editor: Konstantina Nikita

Copyright © 2012 Olga Papadodima et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Atherosclerosis is a multifactorial disease involving a lot of genes and proteins recruited throughout its manifestation. The present study aims to exploit bioinformatic tools in order to analyze microarray data of atherosclerotic aortic lesions of ApoE knockout mice, a model widely used in atherosclerosis research. In particular, a dynamic analysis was performed among young and aged animals, resulting in a list of 852 significantly altered genes. Pathway analysis indicated alterations in critical cellular processes related to cell communication and signal transduction, immune response, lipid transport, and metabolism. Cluster analysis partitioned the significantly differentiated genes in three major clusters of similar expression profile. Promoter analysis applied to functional related groups of the same cluster revealed shared putative cis-elements potentially contributing to a common regulatory mechanism. Finally, by reverse engineering the functional relevance of differentially expressed genes with specific cellular pathways, putative genes acting as hubs, were identified, linking functionally disparate cellular processes in the context of traditional molecular description.

Autor: Olga Papadodima, Allan Sirsjö, Fragiskos N. Kolisis, and Aristotelis Chatziioannou



Documentos relacionados