Evidence map›Paper›PMID 37090432›Full record

ArticleComputational and structural biotechnology journal2023

CDEMI: Characterizing differences in microbial composition and function in microbiome data.

Lidan Wang, Xiao Liang, Hao Chen, Lijie Cao, Lan Liu, Feng Zhu, Yubin Ding, Jing Tang, Youlong Xie

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Lidan WangSchool of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
Xiao LiangSchool of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
Hao ChenSchool of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
Lijie CaoSchool of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
Lan LiuSchool of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
Feng ZhuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Yubin DingDepartment of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing 401147, China.
Jing TangSchool of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
Youlong XieJoint International Research Laboratory of Reproductive and Development, Department Reproductive Biology, School of Public Health, Chongqing Medical University, Chongqing 400016, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial communities influence host phenotypes through microbiota-derived metabolites and interactions between exogenous active substances (EASs) and the microbiota. Owing to the high dynamics of microbial community composition and difficulty in microbial functional analysis, the identification of mechanistic links between individual microbes and host phenotypes is complex. Thus, it is important to characterize variations in microbial composition across various conditions (for example, topographical locations, times, physiological and pathological conditions, and populations of different ethnicities) in microbiome studies. However, no web server is currently available to facilitate such characterization. Moreover, accurately annotating the functions of microbes and investigating the possible factors that shape microbial function are critical for discovering links between microbes and host phenotypes. Herein, an online tool, CDEMI, is introduced to discover microbial composition variations across different conditions, and five types of microbe libraries are provided to comprehensively characterize the functionality of microbes from different perspectives. These collective microbe libraries include (1) microbial functional pathways, (2) disease associations with microbes, (3) EASs associations with microbes, (4) bioactive microbial metabolites, and (5) human body habitats. In summary, CDEMI is unique in that it can reveal microbial patterns in distributions/compositions across different conditions and facilitate biological interpretations based on diverse microbe libraries. CDEMI is accessible at http://rdblab.cn/cdemi/.

Indexed as

Functional characterizationMetabolic pathwayMicrobial associationMicrobial compositionMicrobiome

Identifiers

PMID37090432
PMCPMC10113763

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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.