Evidence map›Paper›PMID 24124405›Full record

ReviewGenomics & informatics2013

Analytical tools and databases for metagenomics in the next-generation sequencing era.

Mincheol Kim, Ki-Hyun Lee, Seok-Whan Yoon, Bong-Soo Kim, Jongsik Chun, Hana Yi

Abstract readReview
In one paragraph

Review in Genomics & informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

  1. Article
  2. Review
  3. Bacterial diversity in the aquatic system in India based on metagenome analysis-a critical review.Environmental science and pollution research international · 2023
    Review
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  10. Review
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  14. Review
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  19. Review
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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

6 authors.

Mincheol KimSchool of Biological Sciences & Institute of Bioinformatics (BIOMAX), Seoul National University, Seoul 151-742, Korea.
Ki-Hyun Lee
Seok-Whan Yoon
Bong-Soo Kim
Jongsik Chun
Hana Yi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.

Indexed as

computational biologyhigh-throughput nucleotide sequencingmetagenomics

Identifiers

PMID24124405
PMCPMC3794082

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.