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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CanPredict: a computational tool for predicting cancer-associated missense mutations.
PMID 17537827 · PMC1933186 · Nucleic acids research · 2007 · 8 claims · 7 setups
CanPredict is a web application providing public access to a random forest classifier that combines SIFT, LogR.E-value, and GOSS scores to predict whether a missense mutation is cancer-associated
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Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups
CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.
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AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes.
PMID 17485433 · PMC5947781 · Bioinformatics (Oxford, England) · 2007 · 7 claims · 2 setups
AutoCSA is an automated algorithm, extended from the CSA protocol, that detects DNA sequence variants in cancer genomes with minimal manual intervention
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Exhaustive prediction of disease susceptibility to coding base changes in the human genome.
PMID 18793467 · PMC2537574 · BMC bioinformatics · 2008 · 8 claims · 7 setups
Inter-species conservation is the strongest single predictor of disease-associated coding mutations among the factors tested.
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Has reproduction · 71
Comprehensive analysis of a novel RNA modifications-related model in the prognostic characterization, immune landscape and drug therapy of bladder cancer.
PMID 37124622 · PMC10131083 · Frontiers in genetics · 2023 · 7 claims · 8 setups
Two distinct RNA modification patterns exist among BCa samples with radically different clinical outcomes and biological characteristics.
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Has reproduction · 83
Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.
PMID 39856156 · PMC11760357 · Scientific reports · 2025 · 8 claims · 8 setups
Ten multiomics clustering algorithms identify two distinct lactylation cancer subtypes (CS1 and CS2) in LUAD
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Has reproduction · 58
iCOMIC: a graphical interface-driven bioinformatics pipeline for analyzing cancer omics data.
PMID 35899080 · PMC9310080 · NAR genomics and bioinformatics · 2022 · 8 claims · 4 setups
iCOMIC provides a GUI-driven, Snakemake-based pipeline integrating multiple tools for DNA-Seq and RNA-Seq analysis with minimal command-line interaction.
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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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Has reproduction · 73
Comprehensive analysis of mitophagy in HPV-related head and neck squamous cell carcinoma.
PMID 37161060 · PMC10170109 · Scientific reports · 2023 · 8 claims · 8 setups
In HPV-associated HNSCC, the mitophagy process affects tumour development, immune cell infiltration and prognosis.
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Has reproduction
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
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.
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Metabolomic profiling in LRRK2-related Parkinson's disease.
PMID 19847307 · PMC2761616 · PloS one · 2009 · 7 claims · 3 setups
Metabolomic profiles of both idiopathic PD and LRRK2 PD are clearly separated from controls
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Machine-learning approaches for classifying haplogroup from Y chromosome STR data.
PMID 18551166 · PMC2396484 · PLoS computational biology · 2008 · 8 claims · 5 setups
Y-STR allelic variability is partitioned more by differences among haplogroups than by differences among populations, suggesting Y-STRs carry haplogroup information