ArticleGenes2021
Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities.
Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
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- Optimization-based framework with flux balance analysis (FBA) and metabolic pathway analysis (MPA) for identifying metabolic objective functions.PLoS computational biology · 2025Article
- An eco-evolutionary perspective on antimicrobial resistance in the context of One Health.iScience · 2025Review
- Microbial interactions shape cheese flavour formation.Nature communications · 2023Article
- Article
- Molecular Methodologies for Improved Polymicrobial Sepsis Diagnosis.International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The behaviour of microbial communities depends on environmental factors and on the interactions of the community members. This is also the case for urinary tract infection (UTI) microbial communities. Here, we devise a computational approach that uses indices of complementarity and competition based on metabolic gene annotation to rapidly predict putative interactions between pair of organisms with the aim to explain pairwise growth effects. We apply our method to 66 genomes selected from online databases, which belong to 6 genera representing members of UTI communities. This resulted in a selection of metabolic pathways with high correlation for each pairwise combination between a complementarity index and the experimentally derived growth data. Our results indicated that
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Registered trials
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