Evidence map›Paper›PMID 41695707›Full record

ArticlePeerJ2026

JGR-NMF: joint graph-regularized non-negative matrix factorization for spatial domain identification.

Juan Liang, Jiuxi Huang, Chenxi Xi, Yun Wang, Juntao Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 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

5 authors.

Juan LiangSchool of Computer Science and Technology, Henan Institute of Technology, Xinxiang, Henan, China.
Jiuxi HuangSchool of Mathematics and Statistics, Henan Normal University, Xinxiang, Henan, China.
Chenxi XiSchool of Mathematics and Statistics, Henan Normal University, Xinxiang, Henan, China.
Yun WangSchool of Mathematics and Statistics, Henan Normal University, Xinxiang, Henan, China.
Juntao LiSchool of Mathematics and Statistics, Henan Normal University, Xinxiang, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spatial transcriptomics technique provides an unprecedented perspective for analyzing the distribution patterns of cells within tissues and their functional tissue structures. To enhance the accuracy and robustness of spatial domain identification, we propose Joint Graph-Regularized Non-negative Matrix Factorization (JGR-NMF). An adaptive neighborhood graph construction strategy is introduced by applying an

Indexed as

Spatial TranscriptomicsAlgorithmsAnimalsBreast NeoplasmsFemaleHumansMiceAdjacency matrixNon-negative matrix factorizationSpatial transcriptomics

Identifiers

PMID41695707
PMCPMC12903897

What OpenQuestion 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 OpenQuestion graph.