ArticleNucleic acids research2016
Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 684 papers.
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684 citing papers in PubMed.
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- Molecular determinants associated with resistance to imipenem and imipenem-relebactam in clinical Pseudomonas aeruginosa isolates.BMC genomics · 2026Article
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- Phenotypic convergence and collateral susceptibility development in Pseudomonas aeruginosa under antibiotic exposure in ICU patients.npj antimicrobials and resistance · 2026Article
624 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.
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