Evidence map›Paper›PMID 23670539›Full record

ReviewMolecular systems biology2013

Computational meta'omics for microbial community studies.

Nicola Segata, Daniela Boernigen, Timothy L Tickle, Xochitl C Morgan, Wendy S Garrett, Curtis Huttenhower

Abstract readReview
In one paragraph

Review in Molecular systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 139 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
139citing papers in PubMed, 2 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

139 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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  6. Review
  7. Review
  8. Article
  9. Microbiome and Communication Disorders: A Tutorial for Clinicians.Journal of speech, language, and hearing research : JSLHR · 2025
    Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Microbiome modeling: a beginner's guide.Frontiers in microbiology · 2024
    Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article

79 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.

Nicola SegataBiostatistics Department, Harvard School of Public Health, Boston, MA, USA.
Daniela Boernigen
Timothy L Tickle
Xochitl C Morgan
Wendy S Garrett
Curtis Huttenhower

Funding

Gut microbiota and inflammatory monocytes in colorectal cancerR01CA154426 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI GARRETT, WENDY S. · 2011 to 2025
$5.2M
Functional activity and inter-organismal interactions in the human microbiomeR01HG005969 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI HUTTENHOWER, CURTIS · 2010 to 2012
$1.3M
Disease Initation and the role of DCs in the TRUC Model of ulcerative colitisK08AI078942 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI GARRETT, WENDY S. · 2009 to 2013
$665k
NCI NIH HHS 1R01CA154426NCI NIH HHS R01 CA154426NHGRI NIH HHS 1R01HG005969NHGRI NIH HHS R01 HG005969NIAID NIH HHS K08 AI078942
6 · The paper itself

Abstract

Complex microbial communities are an integral part of the Earth's ecosystem and of our bodies in health and disease. In the last two decades, culture-independent approaches have provided new insights into their structure and function, with the exponentially decreasing cost of high-throughput sequencing resulting in broadly available tools for microbial surveys. However, the field remains far from reaching a technological plateau, as both computational techniques and nucleotide sequencing platforms for microbial genomic and transcriptional content continue to improve. Current microbiome analyses are thus starting to adopt multiple and complementary meta'omic approaches, leading to unprecedented opportunities to comprehensively and accurately characterize microbial communities and their interactions with their environments and hosts. This diversity of available assays, analysis methods, and public data is in turn beginning to enable microbiome-based predictive and modeling tools. We thus review here the technological and computational meta'omics approaches that are already available, those that are under active development, their success in biological discovery, and several outstanding challenges.

Indexed as

Gene Expression Regulation, BacterialMetagenomeSoftwareAlgorithmsBacteriaComputer SimulationGene Expression ProfilingHumansMetagenomicsMicrobial ConsortiaModels, GeneticPhylogeny

Identifiers

PMID23670539
PMCPMC4039370

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.