Evidence map›Paper›PMID 36895758›Full record

ArticleInnovation (Cambridge (Mass.))2023

Shuangbin Xu, Li Zhan, Wenli Tang, Qianwen Wang, Zehan Dai, Lang Zhou, Tingze Feng, Meijun Chen, Tianzhi Wu, Erqiang Hu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Innovation (Cambridge (Mass.)), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 164 papers.

0numbers the graph read from it
0cells of the map it votes in
164citing papers in PubMed
39.9field-weighted citation impact, top 1% of its field
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

164 citing papers in PubMed, 259 citations in OpenAlex.

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104 more citing papers are in PubMed but not listed here.

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

11 authors at 2 institutions in 1 country.

Shuangbin XuDivision of Laboratory Medicine, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China.
Li ZhanDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Wenli TangDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Qianwen WangDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Zehan DaiDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Lang ZhouDivision of Laboratory Medicine, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China.
Tingze FengDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Meijun ChenDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Tianzhi WuDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Erqiang HuDepartment of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
Guangchuang YuDivision of Laboratory Medicine, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China.
Southern Medical University · CNZhujiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The data output from microbiome research is growing at an accelerating rate, yet mining the data quickly and efficiently remains difficult. There is still a lack of an effective data structure to represent and manage data, as well as flexible and composable analysis methods. In response to these two issues, we designed and developed the

Identifiers

PMID36895758
PMCPMC9988672
OpenAlexW4318955149

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.