Evidence mapPaperPMID 41009770Full record

ReviewInternational journal of molecular sciences2025

Computational Metagenomics: State of the Art.

Marco Antonio Pita-Galeana, Martin Ruhle, Lucía López-Vázquez, Guillermo de Anda-Jáuregui, Enrique Hernández-Lemus

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Systematic Review: Long-Read Sequencing in Algal Studies.International journal of molecular sciences · 2026
    Pooled it
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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.

Marco Antonio Pita-GaleanaComputational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
Martin RuhleComputational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.ORCID 0000-0001-6692-8803
Lucía López-VázquezComputational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
Guillermo de Anda-JáureguiComputational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
Enrique Hernández-LemusComputational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.ORCID 0000-0002-1872-1397

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational metagenomics has revolutionized our understanding of the human microbiome, enabling the characterization of microbial diversity, the prediction of functional capabilities, and the identification of associations with human health outcomes. This review provides a concise yet comprehensive overview of state-of-the-art computational approaches in metagenomics, alongside widely used methods and tools employed in amplicon-based metagenomics. It is intended as an introductory resource for new researchers, outlining key methodologies, challenges, and future directions in the field. We discuss recent advances in bioinformatics pipelines, machine learning (ML) models, and integrative frameworks that are transforming our understanding of the microbiome's role in health and disease. By addressing current limitations and proposing innovative solutions, this review aims to outline a roadmap for future research and clinical translation in computational metagenomics.

Indexed as

Computational BiologyMetagenomicsMicrobiotaHumansMachine LearningMetagenome16S sequencingbacterial genomicscomputational metagenomicscomputational toolsmachine learning (ML)microbiomephylogenetic colocation

Identifiers

PMID41009770
PMCPMC12470432

What Socratic 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 Socratic graph.