Evidence map›Paper›PMID 42402329›Full record

ReviewImmunology and cell biology2026

Agentic AI for Spatial Omics.

Gianna Pavilion, Cathrine Mbigidde, Rafael Tubelleza, Priya Ramarao-Milne, Arutha Kulasinghe

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Immunology and cell biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. ICB Special Feature: Highlights of 2025.Immunology and cell biology · 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.

Gianna PavilionFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Woolloongabba, QLD, Australia.
Cathrine MbigiddeFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Woolloongabba, QLD, Australia.
Rafael TubellezaFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Woolloongabba, QLD, Australia.
Priya Ramarao-MilneAustralian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Brisbane, Queensland, Australia.
Arutha KulasingheFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Woolloongabba, QLD, Australia.ORCID https://orcid.org/0000-0003-3224-7350

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This highlight summarises recent advances in agentic artificial intelligence (AI) systems for spatial omics analysis. These systems are compared along two central tensions: autonomy versus accountability, and adaptability versus reproducibility. We argue that progress will depend not on maximising automation, but on defining where autonomy is appropriate.

Indexed as

Artificial IntelligenceComputational BiologyGenomicsAnimalsHumansagentic AIcomputational biologylarge language modelsmulti‐agent systemsspatial omics

Identifiers

PMID42402329
PMCPMC13542735

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.