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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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
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InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale.
PMID 17868464 · PMC2375030 · Genome biology · 2007 · 8 claims · 8 setups
InSite predicts protein-pair-specific binding motifs ('Motif M on protein A binds to protein B') by integrating heterogeneous PPI and motif-motif interaction evidence within a Bayesian network trained by EM
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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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Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.
PMID 18005451 · PMC2216041 · BMC bioinformatics · 2007 · 8 claims · 5 setups
Parepro, an SVM-based method integrating three attribute sets (RD, MI, IE) derived from evolutionary and residue-property information, predicts whether an nsSNP is deleterious or neutral.
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Identification of deleterious non-synonymous single nucleotide polymorphisms using sequence-derived information.
PMID 18588693 · PMC2446391 · BMC bioinformatics · 2008 · 8 claims · 5 setups
A decision tree built on 10 selected sequence-derived features classifies SAPs as Disease or Polymorphism with 82.6% accuracy and 0.607 MCC in cross-validation.
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Biocomputing enters its adolescence.
PMID 15960815 · PMC1175967 · Genome biology · 2005 · 8 claims · 8 setups
A 'match augmentation' algorithm efficiently matches structural motifs by prioritizing functionally significant residues, enabling function prediction between evolutionarily unrelated proteins
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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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Constructing support vector machine ensembles for cancer classification based on proteomic profiling.
PMID 16689692 · PMC5173238 · Genomics, proteomics & bioinformatics · 2005 · 7 claims · 4 setups
CSVME, built by selecting a subset of base SVMs via SVM-RFE ranking and fusing them with a trained upper-layer SVM, achieves better classification performance than an ensemble of all base SVMs.
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Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum.
PMID 16980117 · PMC7159276 · Lancet (London, England) · 2006 · 8 claims · 5 setups
An SVM classifier trained on serum proteomic profiles discriminated patients with active tuberculosis from controls with clinically overlapping conditions
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SePaCS--a web-based application for classification of seroreactivity profiles.
PMID 17478503 · PMC1933220 · Nucleic acids research · 2007 · 8 claims · 4 setups
SePaCS is a freely available web-based tool that trains and applies multiple classification methods (4 Naive Bayes variants, SVM with RBF kernel, LDA, DLDA) to seroreactivity profiles and outputs results as a summary table plus a detailed PDF report
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Decision forest analysis of 61 single nucleotide polymorphisms in a case-control study of esophageal cancer; a novel method.
PMID 16026601 · PMC1637030 · BMC bioinformatics · 2005 · 8 claims · 2 setups
DF-SNPs, a novel adaptation of the Decision Forest method, can classify esophageal cancer cases vs. controls based on SNP genotype data with high concordance, sensitivity, and specificity.
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Has reproduction · 60
Core transcriptional signatures of phase change in the migratory locust.
PMID 31292921 · PMC6881432 · Protein & cell · 2019 · 8 claims · 7 setups
PhaseCore genes defined by AC-PCA contribution to phase differentiation predict phase status with >87.5% accuracy
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HapMap-based study of the 17q21 ERBB2 amplicon in susceptibility to breast cancer.
PMID 17117180 · PMC2360759 · British journal of cancer · 2006 · 6 claims · 5 setups
Common genetic variation (tSNPs and haplotypes) across the 400-kb 17q21 ERBB2 amplicon is not associated with breast cancer risk in British women.
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Has reproduction · 92
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
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.
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An SVM-based system for predicting protein subnuclear localizations.
PMID 16336650 · PMC1325059 · BMC bioinformatics · 2005 · 7 claims · 3 setups
New kernels defined on k-peptide vectors mapped by BLOSUM62-based high-scored pair matrices (D1, D2, D3) improve SVM discrimination of protein subnuclear localization compared to conventional k-peptide encodings.
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Has reproduction · 81
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
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
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Identification of serum biomarkers for colon cancer by proteomic analysis.
PMID 16755300 · PMC2361335 · British journal of cancer · 2006 · 8 claims · 8 setups
Complement C3a des-arg, α1-antitrypsin and transferrin were identified as serum proteins with diagnostic potential for CRC.