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).

• 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

• 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

• What the Phage: a scalable workflow for the identification and analysis of phage sequences.

  PMID 36399058 · PMC9673492 · GigaScience · 2022 · 8 claims · 7 setups

  Has reproduction · 76

  WtP combines 11 tools (14 approaches) for phage prediction in a parallel, containerized Nextflow workflow

  assembled illumina phage-predicted predicted multitool metagenome gene

• spliceJAC: transition genes and state-specific gene regulation from single-cell transcriptome data.

  PMID 36321549 · PMC9627675 · Molecular systems biology · 2022 · 8 claims · 8 setups

  Has reproduction · 53

  spliceJAC uses unspliced and spliced mRNA count matrices to construct cell state-specific gene-gene regulatory interaction (Jacobian) matrices from scRNA-seq data

  bistable three-gene emt circuits simulation mixed-state grn

• Speeding disease gene discovery by sequence based candidate prioritization.

  PMID 15766383 · PMC1274252 · BMC bioinformatics · 2005 · 7 claims · 8 setups

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  Disease genes (OMIM) differ significantly from non-disease genes in sequence-based features including gene/cDNA/protein size, exon number, homolog conservation, secretion signal, 3' UTR length, CpG islands, and distance to nearest gene.

  ensembl training same hgmd comparative machine tenfold

• GeneExt: a gene model extension tool for enhanced single-cell RNA-seq analysis.

  PMID 41769841 · PMC12970594 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups

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  Incomplete/inaccurate gene annotations, especially missing or truncated 3' UTRs, cause reads to map to non-genic regions and genes to be under-quantified or missing from scRNA-seq expression matrices in non-model species

  genomes whole-organism xenia octopus peak scrna-seq

• Cell neighborhood topology directs rare cell population identification.

  PMID 41912521 · PMC13199379 · Nature communications · 2026 · 8 claims · 8 setups

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  RareQ is a framework that quantifies neighborhood connectivity (Q), a cell-specific measure of kNN-graph cliquishness, to detect rare cell populations from single-cell and spatial omics data

  downsampled pbmc brain simulated scrna-seq cite-seq single-cell