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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Illuminating cell states by a comprehensive and interpretable single cell foundation model.
PMID 41839876 · PMC13139411 · Nature communications · 2026 · 6 claims · 6 setups
CellVQ, incorporating a Single-Cell Discretization (SCD) module that converts cell embeddings into a discrete 'cell code' via a unified codebook, mitigates data heterogeneity and batch effects while improving interpretability
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Has reproduction · 73
Integrated multiomic analysis reveals disulfidptosis subtypes in glioblastoma: implications for immunotherapy, targeted therapy, and chemotherapy.
PMID 38504986 · PMC10950096 · Frontiers in immunology · 2024 · 8 claims · 8 setups
Consensus clustering on 32 disulfidptosis-associated genes stratifies GBM patients into two subtypes, DRGcluster A and B, with distinct survival outcomes.
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EpiXFormer: a cross-attention neural network for predicting cell type-specific transcription factor binding sites.
PMID 41527854 · PMC12796812 · Briefings in bioinformatics · 2026 · 8 claims · 8 setups
EpiXFormer achieves high accuracy (mean AUROC ~0.99) predicting binding sites of both TFs and non-sequence-specific DBPs across 199 DBP-cell type pairs
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Has reproduction · 59
Nucleosome regulatory dynamics in response to TGFβ.
PMID 24771338 · PMC4066760 · Nucleic acids research · 2014 · 8 claims · 7 setups
SuMMIt, a Bayesian strand-based mixture model requiring support from both ends of sequenced fragments, enables precise nucleosome mid-position calling, fuzziness scoring and between-condition change detection.
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A unified framework for correcting batch effects and integrating multi-omics data.
PMID 41786846 · PMC13079841 · Scientific reports · 2026 · 7 claims · 6 setups
MoDAmix, a four-stage domain adaptation framework (pre-training, single-omics adversarial adaptation, multi-omics adversarial alignment, semi-supervised class alignment), unifies batch correction across multiple omics layers.