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).

• 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

  Has reproduction · 78

  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

  tcga degs cd4-gzma prognostic scrna-seq cibersortx differential

• Differential Infiltration of Key Immune T-Cell Populations Across Malignancies Varying by Immunogenic Potential and the Likelihood of Response to Immunotherapy.

  PMID 39682743 · PMC11640164 · Cells · 2024 · 8 claims · 5 setups

  Has reproduction

  Estimated T-cell infiltration differs significantly across melanoma, bladder, ovarian, and pancreatic cancers, tracking known immunogenic potential.

  tumor melanoma orien bulk gene kaplan-meier

• Bulk and single-cell characterisation of the immune heterogeneity of atherosclerosis identifies novel targets for immunotherapy.

  PMID 36855107 · PMC9974063 · BMC biology · 2023 · 8 claims · 8 setups

  Has reproduction · 70

  Integration of scRNA-seq datasets from human atherosclerosis samples identifies 28 distinct immune cell subpopulations with heterogeneity in tissue preference, genetics, function, immune dynamics, transcriptional regulators, metabolism, and cell communication.

  immune atherosclerotic cd4+ cd8+ scrna-seq gsea pseudotime

• An individualized causal framework for learning intercellular communication networks that define microenvironments of individual tumors.

  PMID 36548438 · PMC9822106 · PLoS computational biology · 2022 · 8 claims · 6 setups

  Has reproduction · 67

  An individualized Bayesian causal discovery framework can learn tumor-specific intercellular communication networks (ICNs) by combining single-cell gene expression module (GEM) discovery, bulk tumor deconvolution, and individualized causal network learning.

  hnscc cd45+ cd8+ tcga single-cell bulk pseudo-time