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 · 30
Minimal metabolic pathway structure is consistent with associated biomolecular interactions.
PMID 24987116 · PMC4299494 · Molecular systems biology · 2014 · 8 claims · 8 setups
MinSpan, a mixed-integer linear optimization algorithm, computes the shortest, linearly independent pathways (sparsest basis of the null space of the stoichiometric matrix S) for genome-scale metabolic networks, which convex approaches (extreme pathways, elementary flux modes) cannot do at genome scale.
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Non-linear mapping for exploratory data analysis in functional genomics.
PMID 15661072 · PMC548129 · BMC bioinformatics · 2005 · 8 claims · 8 setups
A relaxation method for non-linear mapping adapts one pair of points per step rather than all points at once, and was originally shown by Chang and Lee to outperform Sammon's mapping in cluster detection effectiveness and computational efficiency.
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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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Large-scale structural analysis of the core promoter in mammalian and plant genomes.
PMID 16049029 · PMC1181242 · Nucleic acids research · 2005 · 8 claims · 7 setups
DNA encodes at least two independent levels of functional information: protein/TF-binding sequence information and physical/structural properties of the molecule itself.
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On the analysis of glycomics mass spectrometry data via the regularized area under the ROC curve.
PMID 18076765 · PMC2211327 · BMC bioinformatics · 2007 · 8 claims · 4 setups
The TGDR-AUC algorithm regularizes the empirical AUC by replacing the non-differentiable 0-1 loss with a smooth sigmoid surrogate function and applies constrained threshold gradient descent regularization