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 · 89
miRge 2.0 for comprehensive analysis of microRNA sequencing data.
PMID 30153801 · PMC6112139 · BMC bioinformatics · 2018 · 8 claims · 6 setups
miRge 2.0 introduces a novel SVM-based miRNA detection method using both hairpin structure and isomiR composition, yielding higher specificity for miRNA identification
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Predictive genomics of cardioembolic stroke.
PMID 19064790 · PMC2752697 · Stroke · 2009 · 8 claims · 4 setups
A Bayesian network multivariate model achieves 86% predictive accuracy (AUC) for cardioembolic stroke on fitted values
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A network model for the correlation between epistasis and genomic complexity.
PMID 18648534 · PMC2481279 · PloS one · 2008 · 8 claims · 5 setups
In small networks with multifunctional nodes, lack of redundancy, and absence of alternative pathways, epistasis is antagonistic on average.
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Threshold-dominated regulation hides genetic variation in gene expression networks.
PMID 18062810 · PMC2238762 · BMC systems biology · 2007 · 8 claims · 2 setups
Threshold robustness (insensitivity of a singular/regulating variable's equilibrium value to parameter perturbations, except threshold changes) increases with increasing response function steepness and is present even under Michaelis-Menten conditions, not just in the step-function limit.
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Has reproduction · 42
CanCellCap: robust cancer cell capture across tissue types on single-cell RNA-seq data by multi-domain learning.
PMID 40739511 · PMC12312500 · BMC biology · 2025 · 8 claims · 8 setups
CanCellCap, a multi-domain learning framework integrating domain adversarial learning and Mixture of Experts, identifies cancer cells across all tissues, cancers, and sequencing platforms by extracting tissue-common and tissue-specific gene expression patterns.
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Has reproduction · 96
GC-biased gene conversion conceals the prediction of the nearly neutral theory in avian genomes.
PMID 30616647 · PMC6322265 · Genome biology · 2019 · 8 claims · 6 setups
gBGC conceals the correlation between life-history traits and dN/dS in birds; accounting for it reveals correlations consistent with nearly neutral theory
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Has reproduction · 67
Evaluating native-like structures of RNA-protein complexes through the deep learning method.
PMID 36828844 · PMC9958188 · Nature communications · 2023 · 8 claims · 7 setups
DRPScore identifies native-like RNA-protein structures with higher success rates than ITScore-PR, DARS-RNP, and 3dRPC across bound and unbound testing sets.
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Gene loss rate: a probabilistic measure for the conservation of eukaryotic genes.
PMID 17158152 · PMC1802574 · Nucleic acids research · 2007 · 8 claims · 8 setups
GLR is a novel maximum-likelihood measure of gene loss rate that probabilistically weighs all possible ancestral phyletic patterns rather than relying on a single parsimonious reconstruction.
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Adaptations to climate in candidate genes for common metabolic disorders.
PMID 18282109 · PMC2242814 · PLoS genetics · 2008 · 8 claims · 7 setups
A network-based bioinformatics approach (Molecular Triangulation) was used to select 82 candidate genes belonging to the core subnetwork of metabolic syndrome phenotypes.
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Automated recognition of retroviral sequences in genomic data--RetroTector.
PMID 17636050 · PMC1976444 · Nucleic acids research · 2007 · 8 claims · 8 setups
RetroTector uses 'fragment threading' (detection of chains of conserved retroviral motifs satisfying distance constraints) combined with LTR detection and protein reconstruction to identify ERVs in genomic sequences
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Has reproduction · 85
Digital sorting of complex tissues for cell type-specific gene expression profiles.
PMID 23497278 · PMC3626856 · BMC bioinformatics · 2013 · 8 claims · 8 setups
The Digital Sorting Algorithm (DSA) deconvolves mixed tissue expression into cell type-specific profiles using only marker genes, without requiring prior knowledge of cell type frequencies or in vitro pure-cell profiles.