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).

• A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability.

  PMID 19941644 · PMC2789744 · BMC bioinformatics · 2009 · 7 claims · 4 setups

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  Feature variability strongly influences breast cancer signature composition even when array platform and patient stratification are identical.

  breast preprocessed microarray two-color perturbation

• MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features.

  PMID 17553836 · PMC1933124 · Nucleic acids research · 2007 · 8 claims · 8 setups

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  A hybrid feature combining local contiguous triplet structure-sequence composition, MFE of the secondary structure, and P-value of a randomization test improves classification of real vs pseudo pre-miRNAs

  real combined pre-mirna training random independent repeated

• On consensus biomarker selection.

  PMID 17570864 · PMC1892093 · BMC bioinformatics · 2007 · 7 claims · 2 setups

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  Four popular feature ranking criteria (t-statistic, mutual information, peak probability contrasts, random forest variable importance) produce different rankings of the same features on the same dataset.

  serum seldi-tof maldi-tof

• Tracing truth: dynamic temporal networks for multi-modal fake news detection.

  PMID 40989433 · PMC12453775 · PeerJ. Computer science · 2025 · 8 claims · 5 setups

  Has reproduction · 33

  The proposed dynamic temporal network (DTN) model improves multi-modal fake news detection accuracy by capturing temporal dynamics of propagation nodes and dynamically fusing multi-modal information.

  news news-related users social text image social

• Automatic discovery of 100-miRNA signature for cancer classification using ensemble feature selection.

  PMID 31533612 · PMC6751684 · BMC bioinformatics · 2019 · 7 claims · 8 setups

  Has reproduction · 69

  An ensemble feature selection method based on classifier consensus identifies a robust 100-miRNA signature from TCGA data.

  tcga geo 100-mirna mirna feature bibliographic

• Artificial Intelligence Meets Whole Slide Images: Deep Learning Model Shapes an Immune-Hot Tumor and Guides Precision Therapy in Bladder Cancer.

  PMID 36245985 · PMC9553530 · Journal of oncology · 2022 · 6 claims · 8 setups

  Has reproduction

  A deep learning WSI cluster (three-class mini batch K-means on Inception V3 features) is associated with overall survival (P<0.001) and is an independent prognostic predictor (P=0.031) in BLCA.

  tcga-blca blca tcga deep transfer-learning neural-network

• Speeding disease gene discovery by sequence based candidate prioritization.

  PMID 15766383 · PMC1274252 · BMC bioinformatics · 2005 · 7 claims · 8 setups

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  Disease genes (OMIM) differ significantly from non-disease genes in sequence-based features including gene/cDNA/protein size, exon number, homolog conservation, secretion signal, 3' UTR length, CpG islands, and distance to nearest gene.

  ensembl training same hgmd comparative machine tenfold

• Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy.

  PMID 16984653 · PMC1618409 · BMC bioinformatics · 2006 · 8 claims · 6 setups

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  The proposed feature set outperforms existing published feature sets for predicting effects of amino acid substitutions

  coli bacteriophage lac proteins svm simulated pearson

• A modified T-test feature selection method and its application on the HapMap genotype data.

  PMID 18267305 · PMC5054219 · Genomics, proteomics & bioinformatics · 2007 · 7 claims · 4 setups

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  A modified t-test ranking measure, extended to handle nominal SNP genotype data via vector transformation, can effectively rank SNPs by their discriminative capability for population classification.

  hapmap modified f-statistics informativeness

• Optimality driven nearest centroid classification from genomic data.

  PMID 17912341 · PMC1991588 · PloS one · 2007 · 7 claims · 5 setups

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  A theoretical result determines the subset of features of a given size that minimizes the misclassification rate for a nearest-centroid (LDA) classifier, based on equation (4).

  artificial simulated previously-published simulated simulation clinical

• Statistical challenges in preprocessing in microarray experiments in cancer.

  PMID 18829474 · PMC3529914 · Clinical cancer research : an official journal of the American Association for Cancer Research · 2008 · 8 claims · 7 setups

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  Choice of pre-processing method materially changes which features are found significantly associated with survival in the Beer et al. lung cancer microarray dataset

  lung beer individual outlier expression rank-covariance quality-control

• Swarm intelligence based wavelet coefficient feature selection for mass spectral classification: an application to proteomics data.

  PMID 19733729 · PMC2748225 · Analytica chimica acta · 2009 · 8 claims · 4 setups

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  ACA-based wavelet coefficient feature selection can achieve up to 100% classification accuracy on training, validating, and independent testing sets using only 5 selected features.

  blood baseline-corrected 953-dimensional training seldi-tof wavelet ant

• Prognostic biomarker discovery in pancreatic cancer through hybrid ensemble feature selection and multi-omics data.

  PMID 41957754 · PMC13188360 · BioData mining · 2026 · 7 claims · 3 setups

  Has reproduction · 92

  The hEFS framework integrates data subsampling with multiple prognostic models (embedded and wrapper-based), aggregates feature rankings via a voting-theory-inspired approach, and selects the optimal feature subset via Pareto front optimization, eliminating user-defined thresholds.

  pancreatic pdac multi-omics gene monte

• Supervised learning-based tagSNP selection for genome-wide disease classifications.

  PMID 18366619 · PMC2386071 · BMC genomics · 2008 · 7 claims · 2 setups

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  SRFA (Supervised Recursive Feature Addition) is a novel feature selection method combining supervised learning and statistical redundancy measures for SNP selection

  micc narac snp

• Atlas - a data warehouse for integrative bioinformatics.

  PMID 15723693 · PMC554782 · BMC bioinformatics · 2005 · 8 claims · 3 setups

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  Atlas is a biological data warehouse that locally stores and integrates sequences, molecular interactions, homology information, functional annotations, and ontologies

  in-house gene omim genome molecular gene-disease

• Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning.

  PMID 34575658 · PMC8472680 · Journal of personalized medicine · 2021 · 6 claims · 4 setups

  Has reproduction · 86

  A training gene set of 719 unique upregulated DEGs (subtype-specific) can be used to build ML models that classify TNBC into BLIA, BLIS, MES, and LAR subtypes.

  known tnbc unique unknown gene machine term

• Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine.

  PMID 16381612 · PMC1360673 · BMC bioinformatics · 2005 · 7 claims · 7 setups

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  A 32-dimensional triplet structure-sequence feature vector combined with SVM (triplet-SVM) can distinguish real human pre-miRNAs from pseudo pre-miRNA hairpins with ~90% accuracy.

  pre-mirnas test conserved-hairpin cross-species secondary svm cross-species

• Towards the identification of essential genes using targeted genome sequencing and comparative analysis.

  PMID 17052348 · PMC1624830 · BMC genomics · 2006 · 8 claims · 8 setups

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  Phyletic retention (ortholog presence across organisms) is the single most predictive feature of gene essentiality in both E. coli and S. cerevisiae.

  coli cerevisiae comparative machine single-gene

• A comparison of classification methods for predicting Chronic Fatigue Syndrome based on genetic data.

  PMID 19772600 · PMC2765429 · Journal of translational medicine · 2009 · 7 claims · 3 setups

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  The naive Bayes model with the wrapper-based feature selection approach performed best among all predictive models tested for distinguishing CFS from controls.

  subjects naive svm c4.5

• A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.

  PMID 19828085 · PMC2762074 · BMC bioinformatics · 2009 · 7 claims · 1 setups

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  A scale-space based unsupervised feature extraction method combined with SVM classification achieves high accuracy in ovarian cancer detection from serum mass spectra.

  serum high-resolution