Computational Network Inference for Bacterial Interactomics

Since the large-scale experimental characterization of protein-protein interactions (PPIs) is not possible for all species, several computational PPI prediction methods have been developed that harness existing data from other species. While PPI network prediction has been extensively used in eukary...

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Bibliographic Details
Published in:mSystems 2022-04, Vol.7 (2), p.e0145621-e0145621
Main Authors: James, Katherine, Muñoz-Muñoz, Jose
Format: Article
Language:English
Subjects:
Bacteria
cellular network analysis
Computational Biology
data integration
interactome
interologs
Minireview
systems biology
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Summary:Since the large-scale experimental characterization of protein-protein interactions (PPIs) is not possible for all species, several computational PPI prediction methods have been developed that harness existing data from other species. While PPI network prediction has been extensively used in eukaryotes, microbial network inference has lagged behind. However, bacterial interactomes can be built using the same principles and techniques; in fact, several methods are better suited to bacterial genomes. These predicted networks allow systems-level analyses in species that lack experimental interaction data. This review describes the current network inference and analysis techniques and summarizes the use of computationally-predicted microbial interactomes to date.
ISSN:2379-5077
2379-5077
DOI:10.1128/msystems.01456-21