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).

• A statistical approach for array CGH data analysis.

  PMID 15705208 · PMC549559 · BMC bioinformatics · 2005 · 8 claims · 4 setups

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  Existing model-selection criteria (AIC, BIC, and prior ad hoc penalties) are not well adapted to estimating the number of segments in array CGH data

  fibroblast simulated bt474 dissected array numerical

• Visualization of shared genomic regions and meiotic recombination in high-density SNP data.

  PMID 19696932 · PMC2725774 · PloS one · 2009 · 8 claims · 7 setups

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  SNPduo is a command-line (SNPduo++) and web-accessible tool that analyzes and visualizes relatedness between two individuals using identity by state (IBS) from SNP genotypes.

  trio family siblings synthetic snp synthetic mitochondrial

• RESCUE: recovery of unattributed expression patterns in spatial transcriptomics.

  PMID 41963343 · PMC13247165 · Nature communications · 2026 · 8 claims · 5 setups

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  Existing ST analysis methods (segmentation, deconvolution) systematically omit or mislabel a substantial portion of true molecular expression

  synthetic honey simulation merfish segmentation

• Sensitive detection of copy number alterations in low-pass liquid biopsy sequencing data.

  PMID 41838873 · PMC12991053 · Briefings in bioinformatics · 2026 · 8 claims · 3 setups

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  BayesCNA uses Bayesian changepoint (BCP) detection on posterior changepoint probabilities to segment the genome and reconstruct copy number profiles from low-pass liquid biopsy data.

  synthetically cell-line blood sequencing low-pass

• sCellST predicts single-cell gene expression from H& E images.

  PMID 41513659 · PMC12858858 · Nature communications · 2026 · 7 claims · 6 setups

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  sCellST is a weakly supervised (Multiple Instance Learning) deep learning framework that predicts single-cell gene expression from H&E images alone, trained using paired spatial transcriptomics (Visium) and H&E slides

  ovarian kidney prostate breast simulation spot-level nucleus

• Reconstructing single-cell resolution from spatial transcriptomics with CellRefiner.

  PMID 41760664 · PMC13066420 · Nature communications · 2026 · 8 claims · 8 setups

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  CellRefiner is a physical/particle-based model (subcellular element method) that integrates scRNA-seq and spatial transcriptomics data to reconstruct single-cell resolution spatial data

  hypothalamic embryo hippocampus visual merfish seqfish slide-seqv2

• A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145.

  PMID 17939873 · PMC2222656 · BMC bioinformatics · 2007 · 8 claims · 4 setups

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  Yu et al.'s original comparison ran RJaCGH's MCMC sampler for a severely insufficient number of iterations (50 burn-in, 500 total)

  simulated same mcmc-based direct original

• scGeno: a Hidden Markov Model approach to denoise chromosome-scale genotypes from single-cell data.

  PMID 41982479 · PMC13075984 · Bioinformatics advances · 2026 · 7 claims · 4 setups

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  scGeno, a categorical HMM, infers chromosome-level genotype states in mixed-genotype organisms by modeling sequential single-cell allelic expression ratios along chromosomes

  wild-type dnmt1 synthetic embryo single-cell posterior down-sampling