ArticlePeerJ2025
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Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbiology research was conducted for decades before widespread availability of sequencing resources and large culture collection sequence repositories, making it challenging to efficiently identify and validate strains used in historical studies. Similarly, finding commercially available microbe strains similar to strains of interest, or containing target genes of interest found during metagenomic experiments is challenging. Despite tremendous advances in sequencing data availability, database curation, and sequence-searching software capabilities, identifying commercially available microbe strains from sequence data remains complicated and tedious. The American Type Culture Collection (ATCC) is an organization selling a wide variety of microbes, uniquely providing strain-level taxonomy classification and associated sequenced reference genomes for over four thousand isolates, with more being added regularly. As researchers purchase and sequence isolates from ATCC, many sequences derived from ATCC isolates are deposited on public databases such as NCBI-Genome. Sequences uploaded to public databases will vary in laboratory, bioinformatics, and metadata quality and can also contain mutations derived from cultivation which are not representative of ATCC stocks. Using ATCC-sourced reference genomes ensures consistent quality and analysis methodologies are implemented to accurately represent strain sequences. Currently, ATCC does not provide methods to search for sequence similarity between many query sequences and ATCC genomes. While NCBI-BLAST could be used to search for queries against GenBank, with results filtered for "ATCC" tags, search result quality varies and requires time-consuming sorting. Here we present the software
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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.