Evidence map›Paper›PMID 27199545›Full record

ReviewEvolutionary bioinformatics online2016

Metagenomics, Metatranscriptomics, and Metabolomics Approaches for Microbiome Analysis.

Vanessa Aguiar-Pulido, Wenrui Huang, Victoria Suarez-Ulloa, Trevor Cickovski, Kalai Mathee, Giri Narasimhan

Abstract readReview
In one paragraph

Review in Evolutionary bioinformatics online, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 215 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
215citing papers in PubMed, 5 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

215 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Effect ofNutrients · 2026
    Trial
  7. Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
  14. Observational
  15. Article
  16. Article
  17. Review
  18. Critical Review: The Past, Present, and Future of Small Intestinal Bacterial Overgrowth (SIBO).JGH open : an open access journal of gastroenterology and hepatology · 2026
    Review
  19. Review
  20. Review

155 more citing papers are in PubMed but not listed here.

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.

Vanessa Aguiar-PulidoBioinformatics Research Group (BioRG), School of Computing and Information Sciences, Florida International University, Miami, FL, USA.
Wenrui HuangBioinformatics Research Group (BioRG), School of Computing and Information Sciences, Florida International University, Miami, FL, USA.
Victoria Suarez-UlloaChromatin Structure and Evolution Group (Chromevol), Department of Biological Sciences, Florida International University, Miami, FL, USA.
Trevor CickovskiBioinformatics Research Group (BioRG), School of Computing and Information Sciences, Florida International University, Miami, FL, USA.; Department of Computer Science, Eckerd College, St. Petersburg, FL, USA.
Kalai MatheeBiomolecular Sciences Institute, Florida International University, Miami, FL, USA.; Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA.; Global Health Consortium, Florida International University, Miami, FL, USA.
Giri NarasimhanBioinformatics Research Group (BioRG), School of Computing and Information Sciences, Florida International University, Miami, FL, USA.; Biomolecular Sciences Institute, Florida International University, Miami, FL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbiomes are ubiquitous and are found in the ocean, the soil, and in/on other living organisms. Changes in the microbiome can impact the health of the environmental niche in which they reside. In order to learn more about these communities, different approaches based on data from multiple omics have been pursued. Metagenomics produces a taxonomical profile of the sample, metatranscriptomics helps us to obtain a functional profile, and metabolomics completes the picture by determining which byproducts are being released into the environment. Although each approach provides valuable information separately, we show that, when combined, they paint a more comprehensive picture. We conclude with a review of network-based approaches as applied to integrative studies, which we believe holds the key to in-depth understanding of microbiomes.

Indexed as

metabolomicsmetagenomicsmetatranscriptomicsmicrobiomenetworks

Identifiers

PMID27199545
PMCPMC4869604

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.