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).

• scGACL: a generative adversarial network with multi-scale contrastive learning for accurate single-cell RNA sequencing imputation.

  PMID 41632596 · PMC12866930 · Briefings in bioinformatics · 2026 · 8 claims · 6 setups

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  scGACL, a GAN integrated with multi-scale contrastive learning, is proposed to overcome the over-smoothing problem in scRNA-seq imputation

  simulated real-world scrna-seq scrna-seq clustering gene

• Evaluating imputation methods for accurate estimation of cell population fractions in single-cell RNA sequencing.

  PMID 41503159 · PMC12770975 · NAR genomics and bioinformatics · 2026 · 8 claims · 6 setups

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  Eight prominent imputation methods (MAGIC, SAVER, scVI, DCA, scBiG, kNN-smoothing, scImpute, ALRA) were systematically evaluated for their ability to recover the true non-zero expression fraction using simulated and real-world scRNA-seq data

  basal tracheal airway k562 simulated scrna-seq imputation

• DeepGSEA: explainable deep gene set enrichment analysis for single-cell transcriptomic data.

  PMID 38950178 · PMC11236288 · Bioinformatics (Oxford, England) · 2024 · 8 claims · 2 setups

  Has reproduction · 40

  DeepGSEA is an explainable deep gene set enrichment analysis method built on interpretable, prototype-based neural networks.

  simulated real-world simulation scrna-seq-based

• Enhancing cell subpopulation discovery in cancer by integrating single-cell transcriptome and expressed variants.

  PMID 41647537 · PMC12869734 · Fundamental research · 2026 · 6 claims · 3 setups

  Has reproduction · 68

  scCluster, an end-to-end deep clustering model integrating gene expression and expressed variant (eSNP) features, stratifies cell subpopulations in cancer scRNA-seq data.

  raw real-world expressed gene deep

• scCNMF: an integrated analysis model for paired single-cell RNA sequencing and assay for transposase-accessible chromatin sequencing data leveraging cell similarity and cis-regulatory potential.

  PMID 41800139 · PMC12962131 · PeerJ · 2026 · 7 claims · 2 setups

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  scCNMF is an NMF-based model for vertical integration of paired scRNA-seq and scATAC-seq data that jointly incorporates a cell similarity matrix and a cis-regulatory potential (CRP) matrix

  publicly 10x paired