Evidence map›Paper›PMID 40161796›Full record

ArticlebioRxiv : the preprint server for biology2025

IAN: An Intelligent System for Omics Data Analysis and Discovery.

Vijayaraj Nagarajan, Guangpu Shi, Reiko Horai, Cheng-Rong Yu, Jaanam Gopalakrishnan, Manoj Yadav, Michael H Liew, Calla Gentilucci, Rachel R Caspi

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

9 authors.

Vijayaraj NagarajanLaboratory of Immunology, National Eye Institute, NIH, Bethesda 20892, USA.ORCID 0000-0003-2455-7172
Guangpu ShiLaboratory of Immunology, National Eye Institute, NIH, Bethesda 20892, USA.
Reiko HoraiLaboratory of Immunology, National Eye Institute, NIH, Bethesda 20892, USA.
Cheng-Rong YuMolecular Immunology Section, National Eye Institute, NIH, Bethesda 20892, USA.
Jaanam GopalakrishnanNeuro-Immune Regulome Unit, National Eye Institute, NIH, Bethesda 20892, USA.
Manoj YadavMolecular Immunology Section, National Eye Institute, NIH, Bethesda 20892, USA.
Michael H LiewNeuro-Immune Regulome Unit, National Eye Institute, NIH, Bethesda 20892, USA.
Calla GentilucciLaboratory of Immunology, National Eye Institute, NIH, Bethesda 20892, USA.
Rachel R CaspiLaboratory of Immunology, National Eye Institute, NIH, Bethesda 20892, USA.

Funding

T-CELL LINES AND CLONES IN UVEITAZ01EY000184 · NEI · NATIONAL EYE INSTITUTE · PI CASPI, RACHEL R. · 1985 to 2008
$6.6M
Understanding the microbial requirements for colonization and immunogenicity of commensal bacteria at the ocular surfaceR01EY032482 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ST LEGER, ANTHONY J · 2021 to 2025
$2.0M
Intramural NIH HHS Z01 EY000184NEI NIH HHS R01 EY032482
6 · The paper itself

Abstract

IAN is an R package that addresses the challenge of integrating, analyzing and interpreting high-throughput "omics" data, using a multi-agent artificial intelligence (AI) system. IAN leverages popular pathway and regulatory datasets (KEGG, WikiPathways, Reactome, GO, ChEA) and the STRING database for protein-protein interactions to perform standard enrichment analysis. The individual enrichment results are then used to generate insightful summaries, for each of the datasets, using a large language model (LLM) through a multi-agent architecture. These summaries are then contextually integrated and interpreted by the LLM, guided by carefully engineered prompts and grounding instructions, to provide insightful explanations, system overview, key regulators, novel observations etc. We demonstrate IAN's potential to facilitate biological discovery from complex omics data, by reanalyzing two already published data and evaluating the results. We also show remarkable performance of IAN, in terms of avoiding hallucination. IAN package, along with installation instructions and example usage, is available on https://github.com/NIH-NEI/IAN.

Identifiers

PMID40161796
PMCPMC11952324

What OpenQuestion holds

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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.