Evidence map›Paper›PMID 41520514›Full record

ReviewCurrent opinion in biotechnology2026

Unlocking therapeutic impacts of the gut microbiota with computational tools.

Anjali Kharb, Xuejun Zhu

Abstract readReview
In one paragraph

Review in Current opinion in biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

2 authors.

Anjali KharbDepartment of Chemical Engineering, Texas A&M University, College Station, TX 77843, United States.
Xuejun ZhuDepartment of Chemical Engineering, Texas A&M University, College Station, TX 77843, United States; Interdisciplinary Graduate Program in Genetics & Genomics, Texas A&M University, College Station, 77843 TX, United States. Electronic address: xjzhu@tamu.edu.

Funding

Discovery and development of drug cocktails evolved by NatureR35GM146984 · NIGMS · TEXAS ENGINEERING EXPERIMENT STATION · PI Xuejun Zhu · 2022 to 2026
$1.7M
NIGMS NIH HHS R35 GM146984
6 · The paper itself

Abstract

The human gut microbiota, particularly the intestinal microbiota, shapes host physiology, disease risk, and therapeutic outcomes through complex metabolic and enzymatic activities. Recent advances in molecular omics, metabolomics, enzyme bioinformatics, and artificial intelligence (AI) have created unprecedented opportunities to elucidate its therapeutic roles to further enable precision microbiome medicine for personalized prevention, diagnosis, and treatment. In this review, we highlight emerging applications that leverage molecular omics and metabolomics technologies to dissect gut microbial functions, along with developments in enzyme bioinformatics and AI tools that reveal gut microbial species, enzymes, and metabolic pathways impacting human health. Finally, we discuss perspectives on data standardization, functional annotation, and interpretability, and how emerging tools are accelerating translational microbiome research.

Indexed as

Computational BiologyGastrointestinal MicrobiomeArtificial IntelligenceHumansMetabolomics

Identifiers

PMID41520514
PMCPMC12836474

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.