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).

• Transcription network construction for large-scale microarray datasets using a high-performance computing approach.

  PMID 18366618 · PMC2386070 · BMC genomics · 2008 · 8 claims · 7 setups

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  RMT removes the random noise component of the gene expression correlation matrix by testing its eigenvalue statistics against a null hypothesis derived from a truly random correlation matrix

  yeast liver eight-node microarray k-means hybrid

• Non-linear mapping for exploratory data analysis in functional genomics.

  PMID 15661072 · PMC548129 · BMC bioinformatics · 2005 · 8 claims · 8 setups

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  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.

  leukaemia small srbct brain relaxation self-organising sammon's

• Network inference and network response identification: moving genome-scale data to the next level of biological discovery.

  PMID 20174676 · PMC3087299 · Molecular bioSystems · 2010 · 8 claims · 8 setups

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  Cellular response to a signal is assumed to involve only specific TRN modules (conditionally active subnetworks) rather than the entire network, providing quantitative tractability

  yeast specified normal coli chip-on-chip chip-sequencing correlation-based

• Minimal metabolic pathway structure is consistent with associated biomolecular interactions.

  PMID 24987116 · PMC4299494 · Molecular systems biology · 2014 · 8 claims · 8 setups

  Has reproduction · 30

  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.

  simplified genome-scale cerevisiae coli minspan spearman comparative

• Adaptations to climate in candidate genes for common metabolic disorders.

  PMID 18282109 · PMC2242814 · PLoS genetics · 2008 · 8 claims · 7 setups

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  A network-based bioinformatics approach (Molecular Triangulation) was used to select 82 candidate genes belonging to the core subnetwork of metabolic syndrome phenotypes.

  individuals population genic compiled snp spearman bayesian