Evidence map›Paper›PMID 30425147›Full record

ArticlemBio2018

Identifying and Predicting Novelty in Microbiome Studies.

Xiaoquan Su, Gongchao Jing, Daniel McDonald, Honglei Wang, Zengbin Wang, Antonio Gonzalez, Zheng Sun, Shi Huang, Jose Navas, Rob Knight and 1 more

Abstract read
In one paragraph

Article in mBio, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  8. Construction of a caries diagnosis model based on microbiome novelty score.Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2023
    Article
  9. Article
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  11. Review
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  18. Bioinformatics advances · 2021
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Xiaoquan SuSingle-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China suxq@qibebt.ac.cn robknight@ucsd.edu xujian@qibebt.ac.cn.
Gongchao JingSingle-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Daniel McDonaldDepartment of Pediatrics, University of California San Diego, La Jolla, California, USA.
Honglei WangSingle-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Zengbin WangSingle-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Antonio GonzalezDepartment of Pediatrics, University of California San Diego, La Jolla, California, USA.
Zheng SunSingle-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Shi HuangSingle-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Jose NavasDepartment of Computer Science & Engineering, University of California San Diego, La Jolla, California, USA.
Rob KnightDepartment of Pediatrics, University of California San Diego, La Jolla, California, USA suxq@qibebt.ac.cn robknight@ucsd.edu xujian@qibebt.ac.cn.
Jian XuSingle-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China suxq@qibebt.ac.cn robknight@ucsd.edu xujian@qibebt.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the expansion of microbiome sequencing globally, a key challenge is to relate new microbiome samples to the existing space of microbiome samples. Here, we present Microbiome Search Engine (MSE), which enables the rapid search of query microbiome samples against a large, well-curated reference microbiome database organized by taxonomic similarity at the whole-microbiome level. Tracking the microbiome novelty score (MNS) over 8 years of microbiome depositions based on searching in more than 100,000 global 16S rRNA gene amplicon samples, we detected that the structural novelty of human microbiomes is approaching saturation and likely bounded, whereas that in environmental habitats remains 5 times higher. Via the microbiome focus index (MFI), which is derived from the MNS and microbiome attention score (MAS), we objectively track and compare the structural-novelty and attracted-attention scores of individual microbiome samples and projects, and we predict future trends in the field. For example, marine and indoor environments and mother-baby interactions are likely to receive disproportionate additional attention based on recent trends. Therefore, MNS, MAS, and MFI are proposed "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.

Indexed as

Computational BiologyDatabases, FactualHumansMicrobiotaPhylogenyRNA, Ribosomal, 16SSequence Analysis, DNARNA, Ribosomal, 16Sbioinformaticscommunity similaritydatabase searchdata miningmicrobial ecologymicrobiomemicrobiome noveltynoveltysearch

Identifiers

PMID30425147
PMCPMC6234870

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.