Evidence map›Paper›PMID 42254512›Full record

ArticleFrontiers in microbiology2026

A transcription unit based systems biology study on

Leting Sun, Zhixuan Deng, Junya Zhang, Xin Cao, Shuhong Liu, Runhong Chen, Min Zheng, Yejun Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Leting SunYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.
Zhixuan DengYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.
Junya ZhangYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.
Xin CaoYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.
Shuhong LiuYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.
Runhong ChenYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.
Min ZhengYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.
Yejun WangYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A bacterial transcription unit (TU) could be composed of a single gene or multiple adjacent genes forming an operon. Traditional systems biology often relies on gene-centric analysis, overlooking the regulatory complexity inherent in the operon structure, that is, containing transcriptional regulatory elements shared by multiple genes within a unique operon. Here, by integrating genome annotation with large-scale transcriptomic profiling data, we systematically identified operons from five representative

Indexed as

core transcription unitoperonoperon evolutionpan transcription unitSalmonella typhimuriumtranscription unit

Identifiers

PMID42254512
PMCPMC13233679

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.