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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Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution.
PMID 41895263 · PMC13106970 · Cell reports methods · 2026 · 8 claims · 5 setups
scRNA-seq references yield significantly higher Pearson correlation and lower RMSE than snRNA-seq references for deconvolution across all four tissue datasets
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Multimodal profiling of pancreatic cancer reveals a TIMP-1-dominated secretory profile determining pro-tumor immunoinstruction in human cancers.
PMID 41564862 · PMC12866174 · Cell reports. Medicine · 2026 · 8 claims · 8 setups
A 19-factor cancer-immunoinstructive secretory signature (CISS) is present across multiple human cancers and correlates with pro-tumorigenic tumor microenvironments and poor patient survival.
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Resolving sensitivity, specificity and signal contamination in Xenium spatial transcriptomics.
PMID 42062553 · PMC13259927 · Nature methods · 2026 · 8 claims · 6 setups
Xenium data show strong consistency across patients and technical replicates, with little technical variation between platforms
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Single-cell resolution of an open chromatin signature in persister tumor cells.
PMID 41485222 · PMC12978573 · Cell reports · 2026 · 8 claims · 8 setups
Single-nucleus multi-omic (snRNA-seq + snATAC-seq) profiling of fallopian tube, treatment-naive, and NACT-treated HGSOC tissue identifies a persister cell signature (PCS) defining the chemotherapy-tolerant state.
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SexTumorDB: a comprehensive resource of sex-dependent tumor landscape at single-cell resolution.
PMID 41741497 · PMC13046873 · Scientific data · 2026 · 7 claims · 8 setups
SexTumorDB is an integrated resource of RNA-seq profiles of non-reproductive tumors at single-cell resolution, curated, processed, and standardized from published datasets
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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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S3RL: Enhancing Spatial Single-Cell Transcriptomics With Separable Representation Learning.
PMID 41556263 · PMC13042551 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026 · 8 claims · 8 setups
S3RL is a separable representation learning framework that denoises sparse spatial transcriptomic data and enhances biologically relevant signals by integrating gene expression, spatial coordinates, and histological image features.
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SA2E: spatial-aware auto-encoder for cell type deconvolution of spatial transcriptomics data.
PMID 41863296 · PMC13070677 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 5 setups
SA2E is a spatial-aware auto-encoder framework for cell-type deconvolution that does not require predefined cell-type biomarkers