Evidence map›Paper›PMID 26184859›Full record

ReviewGenomics, proteomics & bioinformatics2015

Metagenomic surveys of gut microbiota.

Rahul Shubhra Mandal, Sudipto Saha, Santasabuj Das

Abstract readReview
In one paragraph

Review in Genomics, proteomics & bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Review
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  9. Article
  10. Article
  11. Observational
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  16. Article
  17. The interplay between anticancer challenges and the microbial communities from the gut.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2022
    Review
  18. Review
  19. Article
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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

3 authors.

Rahul Shubhra MandalBiomedical Informatics Centre, National Institute of Cholera and Enteric Diseases, Kolkata 700010, India.
Sudipto SahaBioinformatics Centre, Bose Institute, Kolkata 700054, India. Electronic address: ssaha4@jcbose.ac.in.
Santasabuj DasBiomedical Informatics Centre, National Institute of Cholera and Enteric Diseases, Kolkata 700010, India; Division of Clinical Medicine, National Institute of Cholera and Enteric Diseases, Kolkata 700010, India. Electronic address: dasss@icmr.org.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gut microbiota of higher vertebrates is host-specific. The number and diversity of the organisms residing within the gut ecosystem are defined by physiological and environmental factors, such as host genotype, habitat, and diet. Recently, culture-independent sequencing techniques have added a new dimension to the study of gut microbiota and the challenge to analyze the large volume of sequencing data is increasingly addressed by the development of novel computational tools and methods. Interestingly, gut microbiota maintains a constant relative abundance at operational taxonomic unit (OTU) levels and altered bacterial abundance has been associated with complex diseases such as symptomatic atherosclerosis, type 2 diabetes, obesity, and colorectal cancer. Therefore, the study of gut microbial population has emerged as an important field of research in order to ultimately achieve better health. In addition, there is a spontaneous, non-linear, and dynamic interaction among different bacterial species residing in the gut. Thus, predicting the influence of perturbed microbe-microbe interaction network on health can aid in developing novel therapeutics. Here, we summarize the population abundance of gut microbiota and its variation in different clinical states, computational tools available to analyze the pyrosequencing data, and gut microbe-microbe interaction networks.

Indexed as

AnimalsBase SequenceBiodiversityDiabetes Mellitus, Type 2DNA, BacterialGastrointestinal MicrobiomeGastrointestinal TractGenome, BacterialHumansMetagenomicsMicrobial InteractionsRNA, Ribosomal, 16SSequence Analysis, DNADNA, BacterialRNA, Ribosomal, 16S16S rRNADiseaseMicrobial interaction networkOperational taxonomic unitSequencing

Identifiers

PMID26184859
PMCPMC4563348

What OpenQuestion holds

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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.