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).

• Lorentz-regularized interpretable VAE for multi-scale single-cell transcriptomic and epigenomic embeddings.

  PMID 41555918 · PMC12812404 · Frontiers in genetics · 2025 · 7 claims · 5 setups

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  LiVAE, a dual-pathway VAE with Lorentzian geometric regularization between a primary Euclidean pathway and an information-bottleneck pathway, balances local fidelity with global topology coherence in single-cell embeddings

  single-cell same dapp1 benchmarking umap component-wise

• Integrative Learning of Disentangled Representations from Single-Cell RNA-Sequencing Datasets.

  PMID 41971949 · PMC13068006 · Computational and structural biotechnology journal · 2026 · 8 claims · 6 setups

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  spVIPES decomposes unpaired scRNA-seq datasets with nonmatching features into shared and private latent representations using a Product of Experts framework

  simulated zebrafish kidney peripheral simulated cross-species scrna-seq

• ProtoCloud: A prototypical self-explaining model for single-cell analysis.

  PMID 41997134 · PMC13261663 · Cell genomics · 2026 · 8 claims · 8 setups

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  ProtoCloud matches or outperforms existing annotation methods across 11 large-scale datasets, particularly for rare cell types

  diverse pbmc10k pbmc30k tsca scrna-seq latent gene

• 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

• Bayesian inference of RNA velocity incorporating timepoints, lineage bifurcations, and count data.

  PMID 41860983 · PMC13021174 · PLoS computational biology · 2026 · 8 claims · 8 setups

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  VeloVAE significantly outperforms previous RNA velocity methods in data fit, accuracy of inferred differentiation directions, and transcription rate estimation.

  pancreas developing induced embryo scrna-seq

• A unified framework for correcting batch effects and integrating multi-omics data.

  PMID 41786846 · PMC13079841 · Scientific reports · 2026 · 7 claims · 6 setups

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  MoDAmix, a four-stage domain adaptation framework (pre-training, single-omics adversarial adaptation, multi-omics adversarial alignment, semi-supervised class alignment), unifies batch correction across multiple omics layers.

  brain aml same single-cell bulk k-means

• MultiPert: An adversarial alignment and dual attention framework for single-cell multi-omics perturbation prediction.

  PMID 41811907 · PMC12998955 · PLoS computational biology · 2026 · 8 claims · 7 setups

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  MultiPert reliably predicts both perturbed gene expression and protein abundance profiles from single-cell multi-omics data

  thp-1 kidney gse156478 computational zinb-vae autoencoder eccite-seq

• DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data.

  PMID 34261540 · PMC8281595 · Genome medicine · 2021 · 8 claims · 7 setups

  Has reproduction · 84

  DeepProg is a novel ensemble framework of deep-learning and machine-learning approaches that robustly predicts patient survival subtypes using multi-omics data

  cancer breast hepatocarcinoma tcga multi-omics gene rna-seq

• Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.

  PMID 32825264 · PMC7563725 · Biomolecules · 2020 · 6 claims · 7 setups

  Has reproduction · 80

  Combining WGCNA hub genes and VAE 10-dimensional representation as features for an SVM classifier achieves high accuracy in predicting CRC

  colorectal same combined meturquoise microarray differential batch

• Inference of RNA polymerase II transcription dynamics from chromatin immunoprecipitation time course data.

  PMID 24830797 · PMC4022483 · PLoS computational biology · 2014 · 8 claims · 8 setups

  Has reproduction · 75

  A convolved Gaussian process model of pol-II occupancy across gene segments captures the transcription wave and yields estimates of transcription speed and promoter-proximal pol-II activity.

  mcf7 promoter gene signals pol-ii clustering transcription

• 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

• 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

• scATD: a high-throughput and interpretable framework for single-cell cancer drug resistance prediction and biomarker identification.

  PMID 40501071 · PMC12159290 · Briefings in bioinformatics · 2025 · 8 claims · 6 setups

  Has reproduction · 62

  scATD enables high-throughput single-cell drug sensitivity prediction for new patients without model parameter retraining via bidirectional Bi-AdaIN style transfer

  panglaodb cancer geo gse137829 single-cell bulk

• VIST: variational inference for single cell time series.

  PMID 41535949 · PMC12892444 · Genome biology · 2026 · 8 claims · 6 setups

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  VIST is a VAE-based method that decomposes single-cell gene expression into time-dependent and time-independent latent components

  toy drosophila aorta lung synthetic time-course latent

• Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.

  PMID 20019805 · PMC2787626 · PLoS computational biology · 2009 · 8 claims · 8 setups

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  A novel semi-parametric meta-analysis method (based on a gene-centric Glass's d effect size) outperforms existing parametric and non-parametric meta-analysis methods at identifying functionally coherent gene pairs across species.

  liver simulated conserved nearly gene simulation kolmogorov-smirnov

• CanSig Benchmarks Methods for Reproducible Cancer Cell State Discovery from Single-Cell Transcriptomic Data.

  PMID 41231245 · PMC13053056 · Cancer research · 2026 · 7 claims · 7 setups

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  CanSig is a comprehensive benchmarking tool for evaluating computational methods that identify shared transcriptional signatures in cancer from scRNA-seq data

  neftel kim scrna-seq same scrna-seq ground-truth robustness

• Multimodal framework for the joint analysis of single-cell RNA and T cell receptor sequencing data predicts T cell response to cancer immunotherapy.

  PMID 41820396 · PMC13121706 · Nature communications · 2026 · 8 claims · 7 setups

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  TRIM, a conditional multi-modal variational autoencoder integrating paired scRNAseq and scTCRseq data, predicts T cell clonality and transcriptional states at unmeasured tissue sites/timepoints.

  hnscc colorectal pan-cancer tcr paired umap convolutional