ArticleScientific reports2022
Classification of the plant-associated lifestyle of Pseudomonas strains using genome properties and machine learning.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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
11 citing papers in PubMed.
- Review
- Predicting rhizosphere-competence-related catabolic gene clusters in plant-associated bacteria with rhizoSMASH.Nature communications · 2025Article
- Rationally designed microbial communities in agri-food production systems: from research to market.ISME communications · 2025Article
- Article
- Inoculation withPeerJ · 2025Article
- The Growth-Promoting and Colonization of the Pine EndophyticMicroorganisms · 2024Article
- bacLIFE: a user-friendly computational workflow for genome analysis and prediction of lifestyle-associated genes in bacteria.Nature communications · 2024Article
- Comprehensive genome analysis of3 Biotech · 2023Article
- An Efficient Triplex TaqMan Quantitative PCR to Detect a Blackleg-Causing Lineage ofMicroorganisms · 2023Article
- Compositionality, sparsity, spurious heterogeneity, and other data-driven challenges for machine learning algorithms within plant microbiome studies.Current opinion in plant biology · 2023Review
- Coping with salt stress-interaction of halotolerant bacteria in crop plants: A mini review.Frontiers in microbiology · 2023Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rhizosphere, the region of soil surrounding roots of plants, is colonized by a unique population of Plant Growth Promoting Rhizobacteria (PGPR). Many important PGPR as well as plant pathogens belong to the genus Pseudomonas. There is, however, uncertainty on the divide between beneficial and pathogenic strains as previously thought to be signifying genomic features have limited power to separate these strains. Here we used the Genome properties (GP) common biological pathways annotation system and Machine Learning (ML) to establish the relationship between the genome wide GP composition and the plant-associated lifestyle of 91 Pseudomonas strains isolated from the rhizosphere and the phyllosphere representing both plant-associated phenotypes. GP enrichment analysis, Random Forest model fitting and feature selection revealed 28 discriminating features. A test set of 75 new strains confirmed the importance of the selected features for classification. The results suggest that GP annotations provide a promising computational tool to better classify the plant-associated lifestyle.
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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 Socratic graph.