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).

• SurvConvMixer: robust and interpretable cancer survival prediction based on ConvMixer using pathway-level gene expression images.

  PMID 38539106 · PMC10967213 · BMC bioinformatics · 2024 · 6 claims · 5 setups

  Has reproduction · 77

  SurvConvMixer, using pathway-level gene expression images and ConvMixer, achieves strong internal validation AUC for overall survival prediction, especially on larger datasets like LUAD

  luad lusc skcm trained deep benchmark model

• Interpretable and integrative analysis of single-cell multiomics with scMKL.

  PMID 40770488 · PMC12328712 · Communications biology · 2025 · 7 claims · 7 setups

  Has reproduction · 65

  scMKL outperforms SVM, EasyMKL, MLP, and XGBoost in classification accuracy (AUROC) across multiple single-cell cancer datasets

  mcf-7 t-47d small prostate 10x scrna-seq sciatac-seq

• Fast, accurate, and racially unbiased pan-cancer tumor-only variant calling with tabular machine learning.

  PMID 36611079 · PMC9825621 · NPJ precision oncology · 2023 · 7 claims · 8 setups

  Has reproduction

  Tabular ML classifiers (TabNet, XGBoost, LightGBM) trained on tumor-only-derived features achieve state-of-the-art somatic vs germline classification, with AUC>94% on TCGA holdout and AUC>85% on metastatic melanoma.

  tcga metastatic tumor-only whole-exome wes copy-number

• Graph Random Forest: A Graph Embedded Algorithm for Identifying Highly Connected Important Features.

  PMID 37509188 · PMC10377046 · Biomolecules · 2023 · 8 claims · 6 setups

  Has reproduction · 89

  GRF identifies effective features that form highly connected sub-graphs on the underlying biological network

  synthetic tcga embryonic simulation sub-graph reproducibility