Evidence map›Paper›PMID 42363230›Full record

ArticleGenome biology2026

ResSAT: enhancing spatial transcriptomics prediction from H&E-stained histology images with an interactive spot transformer.

Anqi Liu, Yue Zhao, Woong-Ki Kim, Hui Shen, Zhengming Ding, Hong-Wen Deng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Computer Vision Methods for Spatial Transcriptomics: A Survey.bioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Anqi LiuTulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, USA.
Yue ZhaoTulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, USA.
Woong-Ki KimDepartment of Microbiology and Immunology, Tulane University School of Medicine, New Orleans, LA, USA.
Hui ShenTulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, USA.
Zhengming DingDepartment of Computer Science, School of Science and Engineering, Tulane University, New Orleans, LA, USA. zding1@tulane.edu.
Hong-Wen DengTulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, USA. hdeng2@tulane.edu.

Funding

Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Katherine Teresa Mills · 2016 to 2026
$25.3M
Trans-omics Integration of Multi-omics Studies for OsteoporosisU19AG055373 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI Chuan Qiu · 2017 to 2026
$24.3M
Identification of Metabolomic Profiles for Sarcopenia Traits in Older Whites and BlacksR01AG061917 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI SHEN, HUI, ZHAO, QI · 2019 to 2023
$3.0M
National Institue of Health U19AG055373NIA NIH HHS R01 AG061917NIA NIH HHS R01AG061917NIA NIH HHS U19 AG055373NIGMS NIH HHS P20 GM109036NIGMS NIH HHS P20GM109036
6 · The paper itself

Abstract

Spatial transcriptomics has revolutionized RNA quantification with spatial resolution. Hematoxylin and eosin (H&E) images, the gold standard in medical diagnosis, offer insights into tissue structure, correlating with gene expression patterns. We introduce ResSAT (Residual networks with Spatial encoding-self-Attention Transformer), a framework for predicting spatially resolved transcriptomic profiles from H&E images by integrating image features, spatial locations, and self-attention transformer-based spot interactions. Benchmarking on 10 × Visium datasets, ResSAT outperforms existing methods and preserved biologically meaningful spatial patterns, promising reduced spatial transcriptomics profiling costs and rapid acquisition of numerous profiles.

Indexed as

Image Processing, Computer-AssistedSoftwareSpatial TranscriptomicsTranscriptomeEosine Yellowish-(YS)Gene Expression ProfilingHematoxylinHumansStaining and LabelingEosine Yellowish-(YS)HematoxylinHematoxylin and eosin imagesSpatial transcriptomicsTransformer

Identifiers

PMID42363230
PMCPMC13576212

What OpenQuestion holds

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Registered trials

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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.