ArticleNAR genomics and bioinformatics2024
Optimal Representative Strain selector-a comprehensive pipeline for selecting next-generation reference strains of bacterial species.
Article in NAR genomics and bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Assessment of genome evolution inmSystems · 2026Article
- Review
- Host interactions ofApplied and environmental microbiology · 2025Article
- Compiling an early life human gut microbiome atlas and identification of key microbial drivers.NPJ biofilms and microbiomes · 2025Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although it is common practice to use historically established 'reference strains' or 'type strains' for laboratory experiments, this approach often overlooks how effectively these strains represent the full ecological, genetic and functional diversity of the species within a specific ecological niche. In this context, this study proposes the Optimal Representative Strain (ORS) selector tool (https://zenodo.org/doi/10.5281/zenodo.13772191), an innovative bioinformatic pipeline capable of evaluating how a strain represents its whole species from a genetic and functional perspective, in addition to considering its ecological distribution in a particular ecological niche. Based on publicly available genomes, the strain that best fits all these three microbiological aspects is designated as an optimal representative strain. Moreover, a user-friendly software called Local Alternative Optimal Representative Strain selector was developed to allow researchers to screen their local library of bacterial strains for an optimal available alternative based on the reference optimal representative strain. Five different bacterial species, i.e.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.