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).
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Has reproduction · 78
Evaluating Distribution and Prognostic Value of New Tumor-Infiltrating Lymphocytes in HCC Based on a scRNA-Seq Study With CIBERSORTx.
PMID 33043022 · PMC7527443 · Frontiers in medicine · 2020 · 6 claims · 8 setups
CIBERSORTx can combine scRNA-seq-derived signature matrices with bulk RNA-seq data to estimate proportions of 11 TIL subsets in HCC tumor and normal tissue
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Bridging unpaired single-cell multimodal data for integrative analyses with SuperMap.
PMID 41650244 · PMC12890892 · Proceedings of the National Academy of Sciences of the United States of America · 2026 · 8 claims · 7 setups
SuperMap learns cross-modal feature mappings directly from unpaired multimodal data without requiring paired training data
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Evaluating imputation methods for accurate estimation of cell population fractions in single-cell RNA sequencing.
PMID 41503159 · PMC12770975 · NAR genomics and bioinformatics · 2026 · 8 claims · 6 setups
Eight prominent imputation methods (MAGIC, SAVER, scVI, DCA, scBiG, kNN-smoothing, scImpute, ALRA) were systematically evaluated for their ability to recover the true non-zero expression fraction using simulated and real-world scRNA-seq data
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Prior-guided factorization for reliable imputation of scRNA-seq data.
PMID 41860953 · PMC13004523 · PLoS computational biology · 2026 · 8 claims · 8 setups
scZN models scRNA-seq counts as a mixture of a two-state (Gamma-Poisson/negative binomial) transcriptional bursting process and dropout, formalized via a zero-inflated negative binomial (ZINB) and solved as constrained nonnegative matrix factorization into a cell-to-cell-type assignment matrix and a cell-type expression matrix
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ChromBERT: A foundation model for learning interpretable representations for context-specific transcriptional regulatory networks.
PMID 41592570 · PMC13069865 · Cell genomics · 2026 · 8 claims · 7 setups
ChromBERT is pre-trained via masked reconstruction on the Cistrome-Human-6K dataset (6,391 cistromes, 991 transcription regulators) to learn genome-wide interaction syntax of transcription regulators
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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
Senescence-associated marker genes show weak, non-specific expression across human tissues and cell types compared to canonical tissue/cell-type markers
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FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis.
PMID 41839892 · PMC13201544 · Nature communications · 2026 · 8 claims · 6 setups
FineST, a bimodal contrastive learning model integrating histology (Virchow2 ViT features) and spatial gene expression, enables nuclei-resolved high-resolution RNA imputation.
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A unique malignant cell type per patient tumor encoded in each cancer cell transcriptome.
PMID 41884004 · PMC13010111 · iScience · 2026 · 8 claims · 8 setups
Malignant cells cluster predominantly by tumor of origin, while non-malignant cells from the same tumors cluster by cell type independent of patient
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Has reproduction · 67
Leveraging RNA-seq deconvolution to improve complex in vitro model characterization.
PMID 40701251 · PMC12391696 · The Journal of biological chemistry · 2025 · 8 claims · 6 setups
RNA-seq deconvolution can predict cell type proportions from bulk RNA-seq using scRNA-seq references, offering a useful characterization tool for CIVMs where single-cell methods are impractical