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New IDER method improves gene discovery from histology images

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method called image-based differential expression ranking (IDER) to improve the discovery of differentially expressed genes (DEGs) from histology images. This approach focuses on preserving the ranking of genes based on expression differences between biological groups, rather than just reconstructing raw expression magnitudes. IDER utilizes a differentiable objective that aligns gene statistics across contrasts, enabling training with morphology-derived proxy contrasts even without predefined biological labels. Experiments demonstrate that IDER enhances DEG-ranking agreement and pathway-enrichment overlap compared to conventional reconstruction objectives. AI

RANK_REASON The cluster contains an academic paper detailing a new methodology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

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New IDER method improves gene discovery from histology images

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The cluster contains an academic paper detailing a new methodology. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Kaito Shiku, Kazuya Nishimura, Yasuhiro Kojima, Ryoma Bise ·

    Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction

    arXiv:2609.33928v2 Announce Type: replace Abstract: Predicting spatial gene expression from histology images could scale spatial transcriptomics (ST) to image-only cohorts, but conventional histology-based ST prediction is trained and evaluated mainly by per-gene spatial-profile …

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