Evidence map›Paper›PMID 42589656›Full record

ArticleInternational journal of molecular sciences2026

Machine Learning-Guided Stress Atlases Reveal Co-Expression Rewiring and Divergent Cellular Deployment of Abiotic Stress Programs in Rice and Wheat.

Zixuan Wang, Zhouxuan Ge, Haoyu Chao, Alibek Zatybekov, Qirong He, Xiaoying Zheng, Yue Wang, Shilong Zhang, Zhimeng Zhao, Renbo Yao and 3 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 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

13 authors.

Zixuan WangDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Zhouxuan GeDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Haoyu ChaoDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Alibek ZatybekovLaboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan.ORCID 0000-0003-4310-5753
Qirong HeCollege of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310058, China.
Xiaoying ZhengDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0009-0000-9657-2131
Yue WangLaboratory of Fruit Quality Biology, The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Fruit Science Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0003-3263-6794
Shilong ZhangDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Zhimeng ZhaoDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0009-0007-4344-8381
Renbo YaoZhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining 314400, China.
Vladimir A IvanisenkoInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.ORCID 0000-0002-1859-4631
Cong FengDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Ming ChenDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-9677-1699

Funding

Ministry of Science and Technology of the People's Republic of China 2023YFE0112300National Natural Science Foundation of China 32270709; 32570787; 32261133526; 32300532Science and Technology Department of Zhejiang Province 2022R52035
6 · The paper itself

Abstract

Abiotic stress limits cereal productivity, yet whether conserved stress-responsive genes retain similar transcriptional network organization and cellular deployment across cereal species remains unknown. Here, we developed a machine learning-guided comparative framework to integrate public leaf transcriptomes of rice (

Indexed as

Gene Expression Regulation, PlantMachine LearningOryzaStress, PhysiologicalTriticumGene Expression ProfilingGene Regulatory NetworksPlant LeavesPlant ProteinsTranscriptomePlant Proteinsabiotic stressco-expression networkmachine learningricesingle-cell transcriptomicsstress-responsive genestranscriptome atlaswheat

Identifiers

PMID42589656
PMCPMC13466321

What OpenQuestion holds

Textmetadata
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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.