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).

• CanPredict: a computational tool for predicting cancer-associated missense mutations.

  PMID 17537827 · PMC1933186 · Nucleic acids research · 2007 · 8 claims · 7 setups

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  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

  missense observed sjoblom refseq cross-validation recurrence comparative

• Interaction profile-based protein classification of death domain.

  PMID 15189571 · PMC459208 · BMC bioinformatics · 2004 · 7 claims · 6 setups

  Full-text index only

  An SVM-based classifier using Residue Pair Interaction Profiles (RPIPs) can classify death domain superfamily members into subfamilies with 89% average cross-validation accuracy

  homology-modeled death homology putative rigid-body homology model

• ProMiR II: a web server for the probabilistic prediction of clustered, nonclustered, conserved and nonconserved microRNAs.

  PMID 16845048 · PMC1538778 · Nucleic acids research · 2006 · 6 claims · 4 setups

  Full-text index only

  ProMiR II improves on the original ProMiR by integrating free energy, G/C ratio, conservation score and entropy for more controllable miRNA prediction

  genome cytomegalovirus six probabilistic 5-fold directional

• 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

• Hierarchical classification-based pan-cancer methylation analysis to classify primary cancer.

  PMID 38066424 · PMC10709847 · BMC bioinformatics · 2023 · 8 claims · 5 setups

  Has reproduction · 83

  CHCT, a hierarchical classification tool, splits classification of 30 cancer types into ten smaller subproblems using a two-tier architecture to classify primary cancer by methylation profile

  cancer clinical training independent methylation upgma random

• Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach.

  PMID 18834544 · PMC2575220 · BMC bioinformatics · 2008 · 8 claims · 8 setups

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  128 discriminating 4-mer motifs combined with an SVM (RBF kernel, LIBSVM) can distinguish promoter from non-promoter DNA sequences

  plant drosophila promoter same 4-mer tata blast

• Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients.

  PMID 34421903 · PMC8375662 · Frontiers in immunology · 2021 · 8 claims · 8 setups

  Has reproduction · 71

  TB patients show substantial individual variability in the intensity of hallmark IFN responses, as well as in complement system, metabolic, and other pathway responses.

  blood cynomolgus external gene differential principal

• Filtering high-throughput protein-protein interaction data using a combination of genomic features.

  PMID 15833142 · PMC1127019 · BMC bioinformatics · 2005 · 8 claims · 8 setups

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  A combination of three genomic features (interacting Pfam domains, GO annotations, sequence homology) using naive Bayesian networks predicts true protein-protein interactions with high sensitivity and good specificity.

  saccharomyces bank caenorhabditis homo yeast mass naive

• Network-assisted protein identification and data interpretation in shotgun proteomics.

  PMID 19690572 · PMC2736651 · Molecular systems biology · 2009 · 7 claims · 7 setups

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  Confidently identified proteins in a sample form tightly connected sub-networks in the protein interaction network, with significantly higher clustering coefficients than random or topology-matched random sub-networks.

  yeast organs mammary organ shotgun clique-enrichment microarray

• Enhancing chemotherapy response prediction via matched colorectal tumor-organoid gene expression analysis and network-based biomarker selection.

  PMID 39754813 · PMC11754497 · Translational oncology · 2025 · 6 claims · 8 setups

  Has reproduction · 78

  A consensus WGCNA approach combining matched tumor-organoid and independent organoid drug-response expression data identifies gene modules and hub genes predictive of 5-FU chemotherapy response

  colorectal matched combined expression microarray rna-seq consensus

• Constraints to gene flow increase the risk of genome erosion in the Ngorongoro Crater lion population.

  PMID 40258987 · PMC12012037 · Communications biology · 2025 · 8 claims · 9 setups

  Has reproduction · 68

  200 years of quasi-isolation and the 1962 epizootic caused a two-fold increase in inbreeding and an excess of highly deleterious mutations in Crater lions relative to other Greater Serengeti populations

  african lion crater simulated genome principal admixture

• Species-specific protein sequence and fold optimizations.

  PMID 12487631 · PMC139977 · BMC bioinformatics · 2002 · 7 claims · 7 setups

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  Environmental niche is a significant factor explaining variability in amino acid composition across 100 complete genomes

  predicted mean over orf principal hierarchical domain-based

• Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.

  PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups

  Full-text index only

  CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.

  missense same synthetic tp53 random support principal

• Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD.

  PMID 36762572 · PMC10104628 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023 · 7 claims · 7 setups

  Has reproduction · 81

  SCAD, a transfer learning framework integrating adversarial discriminative domain adaptation (ADDA), can infer single-cell drug sensitivities by transferring knowledge from bulk RNA-seq pharmacogenomic data (GDSC) to scRNA-seq target domains

  pan-cancer pc9 451lu a375 bulk scrna-seq computational