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

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

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

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  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

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

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

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  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 multi-omic single-cell landscape of perinatal mouse skin maps lineage specification and reveals shared dynamics in human fetal skin.

  PMID 41998142 · PMC13144478 · Experimental & molecular medicine · 2026 · 7 claims · 8 setups

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  Integrated scATAC/scRNA multi-omics analysis of developing mouse skin identifies gene network axes underlying skin lineage specification

  dorsal scrna-seq skin fibroblast scatac-seq scrna-seq spatial

• Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration.

  PMID 42054434 · PMC13148828 · PLoS computational biology · 2026 · 8 claims · 5 setups

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  SEBULA models the singlet background directly from observed HCLC (high-coverage locus count) statistics using fragment-level snATAC-seq information, avoiding reliance on synthetic/artificial doublets.

  dogma-seq dogma-seq-derived seven snatac-seq q-q density