Network and matrix analysis of the respiratory disease interactome

BMC Systems Biology

Michael Strong¹  Gregory P Cosgrove³  Gargi Datta¹  Benjamin Garcia² 

[1] Computational Bioscience Program, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA;NICTA, Victoria Research Lab, Melbourne, Victoria 3010, Australia;Department of Medicine, National Jewish Health, Denver, CO 80206, USA

关键词: Lung disease;    Respiratory diseases;    Networks;    Interactome;   

Others  :  866635
DOI  :  10.1186/1752-0509-8-34

 received in 2013-11-25, accepted in 2014-03-10,  发布年份 2014

【 摘 要 】

Background

Although respiratory diseases exhibit in a wide array of clinical manifestations, certain respiratory diseases may share related genetic mechanisms or may be influenced by similar chemical stimuli. Here we explore and infer relationships among genes, diseases, and chemicals using network and matrix based clustering methods.

Results

In order to better understand and elucidate these shared genetic mechanisms and chemical relationships we analyzed a comprehensive collection of gene, disease, and chemical relationships pertinent to respiratory disease, using network and matrix based analysis approaches. Our methods enabled us to analyze relationships and make biological inferences among over 200 different respiratory and related diseases, involving thousands of gene-chemical-disease relationships.

Conclusions

The resulting networks provided insight into shared mechanisms of respiratory disease and in some cases suggest novel targets or repurposed drug strategies.

【 授权许可】

   
2014 Garcia et al.; licensee BioMed Central Ltd.

【 图 表 】

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