Evidence map›Paper›PMID 24826073›Full record

ReviewMicrobiology insights2013

The use of metagenomic approaches to analyze changes in microbial communities.

Girish Neelakanta, Hameeda Sultana

Abstract readReview
In one paragraph

Review in Microbiology insights, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Metagenome SNP calling via read-colored de Bruijn graphs.Bioinformatics (Oxford, England) · 2021
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. COThe ISME journal · 2019
    Article
  17. Article
  18. Article
  19. Article
  20. Review
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

2 authors.

Girish NeelakantaCenter for Molecular Medicine, Department of Biological Sciences, Old Dominion University, Norfolk, VA, USA.
Hameeda SultanaCenter for Molecular Medicine, Department of Biological Sciences, Old Dominion University, Norfolk, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbes are the most abundant biological entities found in the biosphere. Identification and measurement of microorganisms (including viruses, bacteria, archaea, fungi, and protists) in the biosphere cannot be readily achieved due to limitations in culturing methods. A non-culture based approach, called "metagenomics", was developed that enabled researchers to comprehensively analyse microbial communities in different ecosystems. In this study, we highlight recent advances in the field of metagenomics for analyzing microbial communities in different ecosystems ranging from oceans to the human microbiome. Developments in several bioinformatics approaches are also discussed in context of microbial metagenomics that include taxonomic systems, sequence databases, and sequence-alignment tools. In summary, we provide a snapshot for the recent advances in metagenomics approach for analyzing changes in the microbial communities in different ecosystems.

Indexed as

bioinformaticsmetagenomicsmicrobial changesmicrobial diversitysequencing

Identifiers

PMID24826073
PMCPMC3987754

What OpenQuestion holds

Textmetadata
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.