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).

• p53 mutations occur in clinical, but not latent, human prostate carcinoma.

  PMID 7737911 · PMC5920585 · Japanese journal of cancer research : Gann · 1995 · 5 claims · 4 setups

  Full-text index only

  p53 point mutations occur in clinical prostate cancer but not in latent (subclinical) prostate carcinoma

  prostate sscp rflp direct

• Partially shared multi-modal embedding learns holistic representation of cell state.

  PMID 41741805 · PMC13021527 · Nature computational science · 2026 · 8 claims · 5 setups

  Full-text index only

  APOLLO automatically learns partial information sharing between multiple data modalities using an autoencoder with a partially overlapping latent space trained via latent optimization.

  simulated paired single simulation scrna-seq multiplexed

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

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

  Full-text index only

  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

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

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

  Full-text index only

  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

• 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

• 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

  Full-text index only

  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

• 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

• Multimodal learning reveals plants' hidden sensory integration logic.

  PMID 41714925 · PMC13032346 · BMC genomics · 2026 · 8 claims · 8 setups

  Full-text index only

  CoMM-BIP (Contrastive Multi-Modal learning with Biologically Informed Priors) integrates transcriptomic, metabolomic, and phenomic data using pathway-guided attention, information-theoretic disentanglement, and domain-aware augmentations

  tomato multimodal transcriptomics metabolomics

• 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

  Full-text index only

  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