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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Has reproduction · 51
Construction and Validation of an Immune Infiltration-Related Gene Signature for the Prediction of Prognosis and Therapeutic Response in Breast Cancer.
PMID 33986754 · PMC8110914 · Frontiers in immunology · 2021 · 7 claims · 8 setups
A 15-gene immune infiltration-related signature (IRS) predicts overall survival in breast cancer, with higher IRS indicating worse prognosis
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Has reproduction · 48
Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature.
PMID 35143511 · PMC8830616 · PloS one · 2022 · 8 claims · 6 setups
A hybrid signature combining the Nottingham Prognostic Index with SIS-selected gene expressions can be built in a data-driven fashion (NPI treated as a gene expression during feature selection).
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Has reproduction · 62
Predicting Bone Metastasis Using Gene Expression-Based Machine Learning Models.
PMID 34858485 · PMC8631472 · Frontiers in genetics · 2021 · 7 claims · 5 setups
A DNN model using the top 34 betweenness-centrality-ranked hub genes predicts bone metastasis with AUC of 92.11% on the GEO validation data.
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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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Has reproduction · 83
Integrative transcriptomic and machine learning framework reveals candidate genes and potential mechanisms of aflatoxin B1 exposure in breast cancer.
PMID 41688730 · PMC12982753 · Scientific reports · 2026 · 7 claims · 8 setups
Twenty-two genes lie at the intersection of AFB1-predicted targets and breast cancer-associated co-expression modules/DEGs
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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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Comparison of prognostic gene expression signatures for breast cancer.
PMID 18717985 · PMC2533026 · BMC genomics · 2008 · 8 claims · 5 setups
The three prognostic signatures (70-gene, 76-gene, GGI) show similar prognostic performance for predicting DMFS despite differing gene identity and development approach
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Has reproduction · 83
Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility.
PMID 26538066 · PMC4634735 · BMC medical genomics · 2015 · 8 claims · 5 setups
A multigene peripheral-blood gene-expression biomarker accurately classifies which women from high-risk families develop familial breast cancer.
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A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data.
PMID 19923232 · PMC2817484 · Nucleic acids research · 2010 · 8 claims · 7 setups
A Perl-based pipeline that BLASTs/BLATs Illumina probe sequences against genomes and transcript databases (RefSeq, UCSC Known Genes, UniGene/GenBank, Ensembl) can classify probes by quality grade (Perfect/Good/Bad/No match) and is applicable across 8 BeadArray platforms and other array types
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Has reproduction · 74
SpaGene: A Deep Adversarial Framework for Spatial Gene Imputation.
PMID 42146899 · PMC13176606 · Computational and structural biotechnology journal · 2026 · 8 claims · 6 setups
SpaGene improves average PCC and SSIM and reduces RMSE compared to 6 baseline methods (SpaGE, gimVI, Tangram, VISTA, spRefine, stDiff) across 8 diverse ST-SC dataset pairs under gene-holdout evaluation.
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Has reproduction · 62
scATD: a high-throughput and interpretable framework for single-cell cancer drug resistance prediction and biomarker identification.
PMID 40501071 · PMC12159290 · Briefings in bioinformatics · 2025 · 8 claims · 6 setups
scATD enables high-throughput single-cell drug sensitivity prediction for new patients without model parameter retraining via bidirectional Bi-AdaIN style transfer