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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Supervised learning-based tagSNP selection for genome-wide disease classifications.
PMID 18366619 · PMC2386071 · BMC genomics · 2008 · 7 claims · 2 setups
SRFA (Supervised Recursive Feature Addition) is a novel feature selection method combining supervised learning and statistical redundancy measures for SNP selection
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Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties.
PMID 16790052 · PMC1534064 · BMC bioinformatics · 2006 · 8 claims · 7 setups
The Sequential Minimal Optimization (SMO) SVM algorithm was the best-performing classifier among 26 WEKA classifiers for predicting catalytic residues
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Automatic discovery of cross-family sequence features associated with protein function.
PMID 16409628 · PMC1395344 · BMC bioinformatics · 2006 · 8 claims · 6 setups
A self-supervised data mining approach can find relationships between sequence features and functional annotations without preconceived functional categories.
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Has reproduction · 88
Comprehensive benchmarking of large language models for RNA secondary structure prediction.
PMID 40205851 · PMC11982019 · Briefings in bioinformatics · 2025 · 7 claims · 4 setups
Existing RNA-LLMs had not previously been evaluated for secondary structure prediction in a unified, fair experimental setup with the same datasets and prediction model.
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Genomic transcriptional profiling identifies a candidate blood biomarker signature for the diagnosis of septicemic melioidosis.
PMID 19903332 · PMC3091321 · Genome biology · 2009 · 6 claims · 5 setups
A candidate 37-transcript diagnostic signature distinguishes septicemic melioidosis from sepsis caused by other organisms with 100% accuracy in the training set and 78%/80% accuracy in two independent validation sets
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Bayesian survival analysis in genetic association studies.
PMID 18617538 · PMC2530885 · Bioinformatics (Oxford, England) · 2008 · 7 claims · 5 setups
A novel Bayesian method (BETA-Surv) extends prior case-control haplotype-clustering work to censored survival outcomes by clustering haplotypes via gene tree/perfect phylogeny topology and relative mutation age.
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A DNA microarray survey of gene expression in normal human tissues.
PMID 15774023 · PMC1088941 · Genome biology · 2005 · 6 claims · 6 setups
Unsupervised hierarchical clustering of gene expression groups normal tissue samples largely according to anatomic location, cellular composition, or physiologic function.
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Glioblastoma subclasses can be defined by activity among signal transduction pathways and associated genomic alterations.
PMID 19915670 · PMC2771920 · PloS one · 2009 · 8 claims · 6 setups
Proteomic analysis of glioma samples reveals three signaling subclasses of GBM associated with predominant EGFR activation, PDGFR activation, or loss of NF1
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MALDI profiling of human lung cancer subtypes.
PMID 19890392 · PMC2767501 · PloS one · 2009 · 8 claims · 8 setups
PIMAC/MALDI-TOF peptide profiles combined with classification models can distinguish normal lung from tumor and differentiate NSCLC histological subtypes
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Extraction of human kinase mutations from literature, databases and genotyping studies.
PMID 19758464 · PMC2745582 · BMC bioinformatics · 2009 · 7 claims · 6 setups
A literature mining pipeline combining MutationFinder, false-positive filtering, and SVM-based classification can extract and disambiguate single-point mutation mentions from abstracts and full text
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Analysis of a set of missense, frameshift, and in-frame deletion variants of BRCA1.
PMID 18992264 · PMC2682550 · Mutation research · 2009 · 8 claims · 8 setups
A combined functional assay, bioinformatics prediction, and structural modeling approach can classify BRCA1 variants of uncertain significance
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A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability.
PMID 19941644 · PMC2789744 · BMC bioinformatics · 2009 · 7 claims · 4 setups
Feature variability strongly influences breast cancer signature composition even when array platform and patient stratification are identical.