Evidence map›Paper›PMID 28321234›Full record

ReviewFrontiers in genetics2017

A Review of Bioinformatics Tools for Bio-Prospecting from Metagenomic Sequence Data.

Despoina D Roumpeka, R John Wallace, Frank Escalettes, Ian Fotheringham, Mick Watson

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 1 pooled it
–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

59 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. International journal of microbiology · 2026
    Review
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  10. The researcher's guide to selecting biomarkers in mental health studies.BioEssays : news and reviews in molecular, cellular and developmental biology · 2024
    Review
  11. Article
  12. Metagenomic sequencing reveals swine lung microbial communities and metagenome-assembled genomes associated with lung lesions-a pilot study.International microbiology : the official journal of the Spanish Society for Microbiology · 2023
    Article
  13. Review
  14. 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

5 authors.

Despoina D RoumpekaThe Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK.
R John WallaceThe Rowett Institute of Nutrition and Health, Department of Life Sciences and Medicine, University of Aberdeen, Aberdeen, UK.
Frank EscalettesIngenza Ltd, Roslin BioCentre, Midlothian, UK.
Ian FotheringhamIngenza Ltd, Roslin BioCentre, Midlothian, UK.
Mick WatsonThe Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The microbiome can be defined as the community of microorganisms that live in a particular environment. Metagenomics is the practice of sequencing DNA from the genomes of all organisms present in a particular sample, and has become a common method for the study of microbiome population structure and function. Increasingly, researchers are finding novel genes encoded within metagenomes, many of which may be of interest to the biotechnology and pharmaceutical industries. However, such "bioprospecting" requires a suite of sophisticated bioinformatics tools to make sense of the data. This review summarizes the most commonly used bioinformatics tools for the assembly and annotation of metagenomic sequence data with the aim of discovering novel genes.

Indexed as

assemblybioinformaticsbioprospectinggene predictionmetagenomicsnext generation sequencing

Identifiers

PMID28321234
PMCPMC5337752

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.