Evidence map›Paper›PMID 41182755›Full record

ArticleBriefings in bioinformatics2025

TaxaGO: a novel, phylogenetically informed gene ontology enrichment analysis tool.

Eleftherios Bochalis, Antonios Papageorgiou, George Lagoumintzis, Dionysios V Chartoumpekis, Ilias Georgakopoulos-Soares

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Phytochemical Characterization ofFood science & nutrition · 2026
    Article
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.

Eleftherios BochalisDivision of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Paediatric Research Institute, 107 W. Dean Keeton Stop C0875, Austin, TX 78712, United States.
Antonios PapageorgiouDivision of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Paediatric Research Institute, 107 W. Dean Keeton Stop C0875, Austin, TX 78712, United States.
George LagoumintzisDivision of Pharmacology and Biosciences, Department of Pharmacy, School of Health Sciences, University of Patras, Patras, 26504, Greece.
Dionysios V ChartoumpekisDivision of Endocrinology, Department of Internal Medicine, School of Medicine, University of Patras, University Campus Rio Achaia, Patras, 26504, Greece.
Ilias Georgakopoulos-SoaresDivision of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Paediatric Research Institute, 107 W. Dean Keeton Stop C0875, Austin, TX 78712, United States.ORCID 0000-0003-3641-1488

Funding

Harnessing the Power of Kmers: Concepts and Methods for Genomic and Proteomic ResearchR35GM155468 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Ilias Georgakopoulos-Soares · 2024 to 2026
$1.2M
NIGMS NIH HHS R35 GM155468
6 · The paper itself

Abstract

The functional interpretation of genes and their protein products across diverse species remains a central challenge in genomics, particularly as datasets grow in scale and complexity. The Gene Ontology (GO) knowledgebase offers a detailed resource of accessing a gene's function. While GO enrichment analysis tools are widely used to uncover biological insights, they are designed for single-species analyses and are not able to integrate phylogenetic relationships into the enrichment analyses. To address this, we created TaxaGO, a high-performance, multi-taxonomic GO enrichment analysis tool that incorporates evolutionary distances with species-level enrichment results to unravel GO enrichment profiles at a taxonomic level. Implemented in Rust for speed and scalability, TaxaGO enables robust cross-species GO enrichment analyses by combining species-specific results through phylogeny-aware statistical frameworks. It supports FASTA and CSV inputs, provides curated background populations for 12 131 species across Archaea, Bacteria, and Eukaryota, and offers advanced features such as count propagation, common ancestor analysis, semantic similarity calculation, and interactive visualizations. When benchmarking against established tools, TaxaGO demonstrates a maximum of 70.33× faster performance and 3.79× reduced memory usage. With an intuitive command-line interface and a user-friendly graphical interface, TaxaGO provides a powerful and accessible platform for functional genomics, evolutionary biology, and systems-level studies across the tree of life.

Indexed as

Computational BiologyGene OntologyPhylogenySoftwareArchaeaDatabases, GeneticGenomicsevolutionary biologygene ontologymultitaxonomic analysesphylogenetic meta-analysis

Identifiers

PMID41182755
PMCPMC12581831

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.