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Dynamical Patterns in Gene Expression Profile After Influenza A Virus Injection

Sherehe Semba, Huiyun Wan, Changgui Gu, HuijieYang

Background: Finding the underlying gene regulatory mechanisms for complex diseases is essential for systems biology. The dynamic mode decomposition is adopted in this article to unveil the coherent dynamical patterns that correspond to viral recognition receptors in time-course gene expression profiles after injection of the Influenza A virus.

Results: The eigenvalues, dynamic modes, and amplitudes provide sufficient clues for distinguishing the symptomatic influenza infection individuals from the asymptomatic ones. The symptomatic individuals have a total of 20 dominant modes having positive real eigenvalues, implying a monotonic increase of the receptor response due to the replication of the virus. The asymptomatic individuals have only two real positive eigenvalues, corresponding to the receptors that activate the innate immune response promoting viral clearance.

Conclusion: If the time-course gene expression profiles are available, one can straightforwardly extend this approach to other diseases, such as COVID-19.