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).

• SpaGene: A Deep Adversarial Framework for Spatial Gene Imputation.

  PMID 42146899 · PMC13176606 · Computational and structural biotechnology journal · 2026 · 8 claims · 6 setups

  Has reproduction · 74

  SpaGene improves average PCC and SSIM and reduces RMSE compared to 6 baseline methods (SpaGE, gimVI, Tangram, VISTA, spRefine, stDiff) across 8 diverse ST-SC dataset pairs under gene-holdout evaluation.

  pairs nanostring st-sc osmfish_zeisel st-sc 5-fold spatially

• iAODE for benchmarking and continuum modeling of single-cell chromatin accessibility.

  PMID 41775921 · PMC13066597 · Communications biology · 2026 · 8 claims · 5 setups

  Full-text index only

  iAODE combines a ZINB-likelihood VAE, a latent Neural ODE, low-weight KL regularization, and an interpretable reconstruction (irecon) bottleneck to learn generative, temporally continuous latent spaces for scATAC-seq.

  simulated real small simulated scatac-seq

• A novel deep learning-driven framework for improving lncRNA comprehensive annotation with LncADeep 2.0.

  PMID 41923359 · PMC13090826 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups

  Full-text index only

  LncADeep 2.0 outperforms LncADeep and other existing tools for lncRNA identification on both GENCODE annotated transcripts and independent RNA-seq data

  lncrna hypertrophic gencode lncrna-protein-mirna mlp-based independent ablation

• DeeReCT-APA: Prediction of Alternative Polyadenylation Site Usage Through Deep Learning.

  PMID 33662629 · PMC9801043 · Genomics, proteomics & bioinformatics · 2022 · 8 claims · 8 setups

  Has reproduction · 50

  DeeReCT-APA quantitatively predicts the usage of all competing PASs of a gene simultaneously, rather than casting the problem as pairwise comparison like prior methods.

  fibroblast genomic same 3'-region 3'-mrna deep

• ICE: robust detection of cellular senescence from weak single-cell signatures using imputation-based marker refinement.

  PMID 41668152 · PMC12990438 · Genome biology · 2026 · 8 claims · 7 setups

  Full-text index only

  Senescence-associated marker genes show weak, non-specific expression across human tissues and cell types compared to canonical tissue/cell-type markers

  tissues pancreas pancreatic brain bulk scrna-seq train

• Dual mechanisms of supporting cell regeneration in the neonatal mouse cochlea.

  PMID 41867623 · PMC13000480 · iScience · 2026 · 8 claims · 8 setups

  Full-text index only

  GER cells regenerate IPhCs through both mitotic and non-mitotic mechanisms

  neonatal lgr5dtr ki67creert2 epcam+ whole-mount edu genetic

• SOX10-regulated promoter use defines isoform-specific gene expression in Schwann cells.

  PMID 32770939 · PMC7430845 · BMC genomics · 2020 · 6 claims · 6 setups

  Has reproduction · 94

  SOX10 binds proximal promoters genome-wide in Schwann cells, with ChIP-seq signal concentrated directly over TSSs that are also marked by H3K4me3

  sciatic schwann gene tn5prime chip-seq tss

• Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine.

  PMID 16381612 · PMC1360673 · BMC bioinformatics · 2005 · 7 claims · 7 setups

  Full-text index only

  A 32-dimensional triplet structure-sequence feature vector combined with SVM (triplet-SVM) can distinguish real human pre-miRNAs from pseudo pre-miRNA hairpins with ~90% accuracy.

  pre-mirnas test conserved-hairpin cross-species secondary svm cross-species

• SiCmiR Atlas: Single-Cell miRNA Landscape Reveals Hub-miRNA and Network Signatures in Human Cancers.

  PMID 41691474 · PMC13042402 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026 · 8 claims · 8 setups

  Full-text index only

  SiCmiR, a two-layer neural network, predicts mature miRNA expression profiles from only 977 LINCS L1000 landmark genes

  tcga k562 pancreatic acth-secreting paired bulk scrna-seq-based

• 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