Evidence map›Paper›PMID 27383682›Full record

ReviewMicrobes and environments2016

Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond.

Satoshi Hiraoka, Ching-Chia Yang, Wataru Iwasaki

Abstract readReview
In one paragraph

Review in Microbes and environments, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. A review of neural networks for metagenomic binning.Briefings in bioinformatics · 2025
    Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Exploring the universal healthy human gut microbiota around the World.Computational and structural biotechnology journal · 2022
    Article
  13. Using metagenomic data to boost protein structure prediction and discovery.Computational and structural biotechnology journal · 2022
    Review
  14. Eukaryotic Cell Capture by Amplified MagneticFrontiers in microbiology · 2021
    Article
  15. Article
  16. Article
  17. Review
  18. A lab in the field: applications of real-time,Biology methods & protocols · 2020
    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

3 authors.

Satoshi HiraokaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, the University of Tokyo.
Ching-Chia Yang
Wataru Iwasaki

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.

Indexed as

BiotaEnvironmental MicrobiologyComputational BiologyMetagenomics

Identifiers

PMID27383682
PMCPMC5017796

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.