Evidence map›Paper›PMID 42181252›Full record

ArticleiScience2026

An intelligent framework for advancing large-scale omics data integration.

Mintian Cui, Shixi Wang, Fan Yang, Yifei Wang, Fanyu Kong, Ni Kong, Mengying Li, Xiaoyue Qiao, Zhen Xu, Ziyu Yan and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2026. 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. 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

13 authors.

Mintian CuiState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Shixi WangState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Fan YangState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Yifei WangState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Fanyu KongDepartment of Internal Emergency Medicine and Critical Care, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
Ni KongState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Mengying LiState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Xiaoyue QiaoState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Zhen XuState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Ziyu YanState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Yu YanState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Jiamo ZhangState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.
Kun ChenState Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200127, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical and biological insights from large-scale omics data are often limited by technical variability and analytical complexity. Here, we present BioinAI, a comprehensive framework that integrates an intelligent system with two algorithms, DeepAdvancer and stNiche, to enable effective data integration. Specifically, DeepAdvancer leverages a class-aware adversarial autoencoder to reconstruct gene expression profiles. When applied to 49,738 samples across 1,016 datasets, it uncovered a transcriptomic continuum and differential trajectory axes, which link diverse diseases through shared immune responses and distinct fate determinants. In the spatial context, stNiche leverages graph networks and symmetry-aware matching to identify functional cellular niches across heterogeneous slides. For instance, it identified a fibroblast-immune niche surrounding hair follicles in healthy skin that is lost in pathological states. BioinAI also provides an online conversational analysis platform, powered by multiple semi-agents, facilitating biological insight extraction from transcriptomic data.

Indexed as

BioinformaticsComputational bioinformaticsTranscriptomics

Identifiers

PMID42181252
PMCPMC13196096

What Socratic holds

Textmetadata
LicenceCC BY
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.