A PubMed-wide associational study of infectious diseases

Vitali Sintchenko*, Stephen Anthony, Xuan Hieu Phan, Frank Lin, Enrico W. Coiera

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
10 Downloads (Pure)


Background:Computational discovery is playing an ever-greater role in supporting the processes of knowledge synthesis. A significant proportion of the more than 18 million manuscripts indexed in the PubMed database describe infectious disease syndromes and various infectious agents. This study is the first attempt to integrate online repositories of text-based publications and microbial genome databases in order to explore the dynamics of relationships between pathogens and infectious diseases. Methodology/Principal Findings: Herein we demonstrate how the knowledge space of infectious diseases can be computationally represented and quantified, and tracked over time. The knowledge space is explored by mapping of the infectious disease literature, looking at dynamics of literature deposition, zooming in from pathogen to genome level and searching for new associations. Syndromic signatures for different pathogens can be created to enable a new and clinically focussed reclassification of the microbial world. Examples of syndrome and pathogen networks illustrate how multilevel network representations of the relationships between infectious syndromes, pathogens and pathogen genomes can illuminate unexpected biological similarities in disease pathogenesis and epidemiology. Conclusions/Significance: This new approach based on text and data mining can support the discovery of previously hidden associations between diseases and microbial pathogens, clinically relevant reclassification of pathogenic microorganisms and accelerate the translational research enterprise.

Original languageEnglish
Article numbere9535
Pages (from-to)1-12
Number of pages12
JournalPLoS ONE
Issue number3
Publication statusPublished - Mar 2010
Externally publishedYes

Bibliographical note

Copyright the Author(s) 2010. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


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