ArticleMicrobial genomics2025
SyFi: generating and using sequence fingerprints to distinguish SynCom isolates.
Article in Microbial genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Bacillus drives functional states in synthetic plant root bacterial communities.Genome biology · 2025Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The plant root microbiome is a complex community shaped by interactions among bacteria, the plant host and the environment. Synthetic community (SynCom) experiments help disentangle these interactions by inoculating host plants with a representative set of culturable microbial isolates from the natural root microbiome. Studying these simplified communities provides valuable insights into microbiome assembly and function. However, as SynComs become increasingly complex to better represent natural communities, bioinformatics challenges arise. Specifically, accurately identifying and quantifying SynCom members based on, for example,
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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.