Frontiers | A review on computational systems biology of pathogen–host interactions | Infectious Diseases

Pathogens manipulate the cellular mechanisms of host organisms via pathogen–host
interactions (PHIs) in order to take advantage of the capabilities of
host cells, leading to infections. The crucial role of these
interspecies molecular interactions in initiating and sustaining
infections necessitates a thorough understanding of the corresponding
mechanisms. Unlike the traditional approach of considering the host or
pathogen separately, a systems-level approach, considering the PHI
system as a whole is indispensable to elucidate the mechanisms of
infection. Following the technological advances in the post-genomic era,
PHI data have been produced in large-scale within the last decade.
Systems biology-based methods for the inference and analysis of PHI
regulatory, metabolic, and protein–protein networks to shed light on
infection mechanisms are gaining increasing demand thanks to the
availability of omics data. The knowledge derived from the PHIs may
largely contribute to the identification of new and more efficient
therapeutics to prevent or cure infections. There are recent efforts for
the detailed documentation of these experimentally verified PHI data
through Web-based databases. Despite these advances in data archiving,
there are still large amounts of PHI data in the biomedical literature
yet to be discovered, and novel text mining methods are in development
to unearth such hidden data. Here, we review a collection of recent
studies on computational systems biology of PHIs with a special focus on
the methods for the inference and analysis of PHI networks, covering
also the Web-based databases and text-mining efforts to unravel the data
hidden in the literature.

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