Evidence map›Paper›PMID 42480539›Full record

ReviewCell genomics2026

Agentic genomics: From pipeline automation to autonomous validation.

Manuel Corpas, Heinner Guio, Segun Fatumo

Abstract readReview
In one paragraph

Review in Cell genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Manuel CorpasSchool of Life Sciences, University of Westminster, London, UK. Electronic address: m.corpas@westminster.ac.uk.
Heinner GuioCentro de Investigación en Bioingeniería (BIO), Universidad de Ingeniería y Tecnología (UTEC), Lima, Perú.
Segun FatumoMRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; Precision Healthcare University Research Institute, Queen Mary University of London, London, UK. Electronic address: s.fatumo@qmul.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomics has entered a phase in which AI agents can autonomously discover, configure, execute, and chain bioinformatics operations from natural-language instructions. We term this paradigm "agentic genomics": the delegation of multi-step genomic analyses to autonomous software agents that select tools, manage dependencies, and adapt execution in response to intermediate results, mediated by large language models (LLMs) and constrained by domain-specific skill libraries. We argue that agentic genomics shifts the bottleneck in computational biology from pipeline construction to validation. We examine emerging systems, including CellAtria, AutoBA, Bio-Copilot, and ClawBio, and assess their divergent architectures. We propose a tiered validation framework spanning research-grade, benchmarked, and clinical-grade analyses and argue that equity-aware design must be a systems requirement rather than an optional aspiration. We identify the infrastructure needed to make agentic genomics trustworthy.

Indexed as

Computational BiologyGenomicsArtificial IntelligenceAutomationHumansLarge Language ModelsSoftware

Identifiers

PMID42480539
PMCPMC13477014

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.