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In Silico Modeling of Granulomatous Diseases #MMPMID27468134
Crouser ED
Curr Opin Pulm Med 2016[Sep]; 22 (5): 500-8 PMID27468134show ga
Purpose of the Review: The pathogenesis of genetically complex granulomatous diseases, such as sarcoidosis and latent tuberculosis, remain largely unknown. With the recent advent of more powerful research tools, such as genome-wide expression platforms, comes the challenge of making sense of the enormous data sets so generated. This manuscript will provide demonstrations of how in silico (computer) analysis of large research data sets can lead to novel discoveries in the field of granulomatous lung disease. Recent Findings: The application of in silico research tools has led to novel discoveries in the fields of non-infectious (e.g., sarcoidosis) and infectious granulomatous diseases. Computer models have identified novel disease mechanisms and can be used to perform ?virtual? experiments rapidly and at low cost compared to conventional laboratory techniques. Summary: Granulomatous lung diseases are extremely complex, involving dynamic interactions between multiple genes, cells and molecules. In silico interpretation of large data sets generated from new research platforms that are capable of comprehensively characterizing and quantifying pools of biological molecules promises to rapidly accelerate the rate of scientific discovery in the field of granulomatous lung disorders.