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WIREs Syst Biol Med
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Using systems biology approaches to understand cardiac inflammation and extracellular matrix remodeling in the setting of myocardial infarction

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Inflammation and extracellular matrix (ECM) remodeling are important components regulating the response of the left ventricle to myocardial infarction (MI). Significant cellular‐ and molecular‐level contributors can be identified by analyzing data acquired through high‐throughput genomic and proteomic technologies that provide expression levels for thousands of genes and proteins. Large‐scale data provide both temporal and spatial information that need to be analyzed and interpreted using systems biology approaches in order to integrate this information into dynamic models that predict and explain mechanisms of cardiac healing post‐MI. In this review, we summarize the systems biology approaches needed to computationally simulate post‐MI remodeling, including data acquisition, data analysis for biomarker classification and identification, data integration to build dynamic models, and data interpretation for biological functions. An example for applying a systems biology approach to ECM remodeling is presented as a reference illustration. WIREs Syst Biol Med 2014, 6:77–91. doi: 10.1002/wsbm.1248 This article is categorized under: Analytical and Computational Methods > Computational Methods Laboratory Methods and Technologies > Proteomics Methods Translational, Genomic, and Systems Medicine > Translational Medicine

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The time course of cardiac healing after myocardial infarction (MI), demonstrating the overlap of processes involved at each time period. About 20 min following MI, myocytes undergo irreversible necrosis and/or apoptosis to induce complement C5a release and initiate an acute inflammation. During the acute response period, infiltrated neutrophils and macrophages release inflammatory mediators and proteinases to degrade extracellular matrix (ECM) and engulf dead tissue debris. Thereafter, granulation tissue is formed, characterized by the presence of macrophages, myofibroblasts, new blood vessels, and ECM components. Eventually, a scar enriched in collagen forms and matures.
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Flow chart of data acquisition, analysis, integration, and interpretation used for systems biology approaches. A portion of this figure was previously published in BMC Systems Biology, Jin Y et al., BioMed Central, © 2011,74 used with permission.
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Comparison between the gene expression levels of 84 extracellular matrix (ECM) genes after myocardial infarction (MI) in the infarct region of saline‐treated mice and three treatment groups (aliskiren—A; valsartan—V; and combination—A + V) for the four most significant layers obtained by sparse singular value decomposition (SSVD) biclustering. The biclustering method was used to find potential ECM biomarkers of cardiac remodeling after MI. The original matrix is shown at the top, the reconstructed matrix containing the four most significant layers is shown in the middle, and the reconstructed matrix containing layer 1 is shown at the bottom. The highlighted columns represent the genes identified as potential ECM biomarkers. Red color indicates that a gene expression is upregulated, whereas dark blue represents downregulation of a gene expression with respect to the expression levels at day 0.
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Analytical and Computational Methods > Computational Methods
Translational, Genomic, and Systems Medicine > Translational Medicine
Laboratory Methods and Technologies > Proteomics Methods

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