Experiments

Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).

• OTMODE: an optimal transport theory-based framework for identifying differential features in single-cell multi-omics data.

  PMID 41335419 · PMC12766913 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups

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  OTMODE, using an unbalanced Sinkhorn algorithm and Wald test, improves differential feature identification in single-cell multi-omics data

  simulated classical degs naive simulated bulk real

• Dynamics and regulation of mitotic chromatin accessibility bookmarking at single-cell resolution.

  PMID 36696508 · PMC9876548 · Science advances · 2023 · 7 claims · 8 setups

  Has reproduction · 50

  Chromatin accessibility continually decreases from mitotic entry until metaphase, then gradually increases as chromosomes segregate.

  l02 tissues hepatoma scatac-seq immunofluorescence atac-see

• CellPredX, a computational framework for cross-data type, cross-sample, and cross-protocol cell type annotation through domain adaptation and deep metric learning.

  PMID 41481570 · PMC12758788 · PLoS computational biology · 2026 · 8 claims · 7 setups

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  CellPredX is a unified semi-supervised framework integrating domain adaptation and deep metric learning to align heterogeneous embeddings for cross-modality cell type annotation.

  pbmc fetal pancreas gse149683 matched unmatched cross-protocol

• A multi-modal diffusion model with dual-cross-attention for multi-omics data generation and translation.

  PMID 41980989 · PMC13253844 · Nature communications · 2026 · 8 claims · 7 setups

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  scDiffusion-X is a multi-modal latent denoising diffusion probabilistic model for single-cell multi-omics data generation, translation, and interpretation.

  openproblem 10x babel miniatlas paired modality augmentation

• Interpretable and integrative analysis of single-cell multiomics with scMKL.

  PMID 40770488 · PMC12328712 · Communications biology · 2025 · 7 claims · 7 setups

  Has reproduction · 65

  scMKL outperforms SVM, EasyMKL, MLP, and XGBoost in classification accuracy (AUROC) across multiple single-cell cancer datasets

  mcf-7 t-47d small prostate 10x scrna-seq sciatac-seq

• Hi-Compass: a depth-aware deep learning framework for predicting cell-type-specific 3D genome organization from single-cell to spatial resolution.

  PMID 41980945 · PMC13250166 · Nature communications · 2026 · 8 claims · 8 setups

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  Hi-Compass predicts cell-type-specific Hi-C contact maps using only ATAC-seq as cell-type-specific input, plus DNA sequence and a generalized CTCF binding profile

  gm12878 curated bulk training hi-c ctcf matched

• Single-cell multiomics uncovers an endothelial mechanosensitive PIEZO1-IL-33 axis driving pulmonary fibrosis.

  PMID 41862476 · PMC13004862 · Nature communications · 2026 · 7 claims · 8 setups

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  Mechanical stress (MS) signaling is significantly elevated in endothelial cells (ECs) from IPF patients and correlates with fibrosis severity and lung function decline

  lung cd31+ single-nucleus scissor meta-analysis

• GAMMI: graph-guided contrastive and adversarial integration of single-cell and spatial multi-omics data.

  PMID 42108634 · PMC13158126 · Briefings in bioinformatics · 2026 · 6 claims · 5 setups

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  GAMMI consistently outperforms state-of-the-art integration methods (GLUE, Harmony, MIDAS, scMoMaT) in biological conservation and batch correction across five mosaic single-cell multi-omics benchmarks

  pbmc postmortem gse138852 gammi-derived multi-omics scrna-seq differential

• A generic reference defined by consensus peaks for single-cell ATAC-seq data analysis.

  PMID 41663439 · PMC12996591 · Nature communications · 2026 · 7 claims · 7 setups

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  Aggregating peaks from 624 high-quality bulk ATAC-seq datasets defines ~1.4 million observed consensus peaks (cPeaks) covering ~30% of the genome.

  bulk scatac-seq cnn gm12878 bulk scatac-seq deep

• Empowering integrative and collaborative exploration of single-cell and spatial multimodal data with SGS genome browser.

  PMID 40233745 · PMC12143324 · Cell genomics · 2025 · 8 claims · 6 setups

  Has reproduction

  SGS is a user-friendly, collaborative, versatile browser for integrative visualization of single-cell and spatial multimodal (scMulti-omics) data

  dorsal hematopoietic brain onek1k sn-m3c-seq scatac-seq spatial

• Development of double-positive thymocytes at single-cell resolution.

  PMID 33771202 · PMC8004397 · Genome medicine · 2021 · 7 claims · 8 setups

  Has reproduction · 86

  DP thymocytes can be classified into blast, rearrangement, and selection subtypes, distinguishable by surface markers CD2 and Ly6d

  thymocytes sorted thymocyte scrna-seq flow immunofluorescence

• Geometry-aware graph attention networks to explain single-cell chromatin states and gene expression with SEAGALL.

  PMID 42026624 · PMC13238118 · Genome biology · 2026 · 8 claims · 6 setups

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  SEAGALL combines a geometry-regularised autoencoder (GRAE) to embed cells and build a cell-cell graph with a graph attention network (GAT) classifier and GNNExplainer-based XAI to identify features driving cell type/phenotype.

  count same scchip-seq ten count latent classification

• Benchmarking LLM-based agents for single-cell omics analysis.

  PMID 41742311 · PMC13064268 · Genome biology · 2026 · 8 claims · 8 setups

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  Introduces a comprehensive benchmarking evaluation system comprising an open-source agent platform, 18 evaluation metrics across four dimensions, and 50 real-world single-cell omics tasks

  agent single-cell spatial scatac-seq llm-agent scrna-seq spatial

• Evaluating the Utilities of Foundation Models in Single-Cell Data Analysis.

  PMID 41869863 · PMC13170260 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026 · 8 claims · 8 setups

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  Among ten/eleven evaluated single-cell FMs, scGPT, Geneformer, and CellFM are the top models considering both performance and user accessibility

  scrna-seq unpaired single-cell scgpt batch multi-omic cell-type