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).

• PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns.

  PMID 41673899 · PMC12998178 · Genome biology · 2026 · 7 claims · 8 setups

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  PreTSA dramatically reduces computational time and memory versus GAM (Monocle, TSCAN) and PseudotimeDE for identifying temporally variable genes (TVGs) while producing highly similar results

  simulated null pbmc pancreas pseudotime tvg false-positive

• Benchmarking LLM-based agents for single-cell omics analysis.

  PMID 41742311 · PMC13064268 · Genome biology · 2026 · 8 claims · 8 setups

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  Introduces a comprehensive benchmarking evaluation system comprising an open-source agent platform, 18 evaluation metrics across four dimensions, and 50 real-world single-cell omics tasks

  agent single-cell spatial scatac-seq llm-agent scrna-seq spatial

• Assessment of dispersion metrics for estimating single-cell transcriptional variability.

  PMID 41770747 · PMC12970974 · PLoS computational biology · 2026 · 7 claims · 4 setups

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  The variance-to-mean ratio (VMR/Fano factor) scales approximately linearly with increasing dispersion and is independent of dataset size.

  simulated manivannan lana-elola yuzwa computational scrna-seq

• Deconvolving cell-type-specific gene expression profiles from bulk RNA-seq samples.

  PMID 41886524 · PMC13038110 · PLoS computational biology · 2026 · 8 claims · 6 setups

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  BLUE, a U-Net-based deep learning model with dual branches (U-Net for GEPs, MLP for proportions), accurately predicts cell-type proportions and cell-type-specific gene expression profiles from bulk RNA-seq.

  pbmc pancreatic aml scrna-seq-derived real scrna-seq

• 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

• Protocol to perform cell-type-specific transcriptome-wide association study using scPrediXcan framework.

  PMID 41689808 · PMC12925207 · STAR protocols · 2026 · 6 claims · 6 setups

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  scPrediXcan enables cell-type-specific transcriptome-wide association studies (TWAS) by integrating deep learning-based prediction of gene expression from DNA sequence and epigenetic features.

  acinar individual-level geuvadis beta mlp-based personalized elastic-net

• ICE: robust detection of cellular senescence from weak single-cell signatures using imputation-based marker refinement.

  PMID 41668152 · PMC12990438 · Genome biology · 2026 · 8 claims · 7 setups

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  Senescence-associated marker genes show weak, non-specific expression across human tissues and cell types compared to canonical tissue/cell-type markers

  tissues pancreas pancreatic brain bulk scrna-seq train

• Intra-Tissue Bacteriome and Cellular Profiles in Periodontal Granulation Tissue From Osseous Defects and Extraction Sockets.

  PMID 41732956 · PMC13086548 · Journal of clinical periodontology · 2026 · 7 claims · 6 setups

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  Osseous defect granulation tissue (GT) and inflamed gingival tissue (PT) exhibit periodontal health-associated, commensal-enriched bacteriome profiles, while root (RT) and socket (ST) granulation tissues show periodontopathogen enrichment and commensal depletion

  periodontal 16s subjects 16s single-cell histology

• Epigenomic, transcriptomic, and proteomic characterization of breast cancer cell line reference samples.

  PMID 41539304 · PMC12853167 · Cell reports methods · 2026 · 8 claims · 5 setups

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  Comprehensive multi-omics reference materials (ATAC-seq, Methyl-seq, RNA-seq, MS-proteomics) were generated for paired HCC1395/HCC1395BL cell lines as a community benchmarking resource

  hcc1395 atac-seq methyl-seq bulk