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).

• Assembling a jigsaw puzzle with 20,000 parts.

  PMID 12801408 · PMC193613 · Genome biology · 2003 · 8 claims · 8 setups

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  Re-routing the intracellular interaction domains of receptor tyrosine kinases can redirect their signaling output, e.g. converting a growth signal into an apoptosis signal.

  yeast caenorhabditis escherichia proteome-wide microarray yeast rnai

• Human synthetic lethal inference as potential anti-cancer target gene detection.

  PMID 20015360 · PMC2804737 · BMC systems biology · 2009 · 7 claims · 8 setups

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  Targeting the synthetic lethal partner of a gene mutated in cancer selectively damages tumor cells while sparing healthy cells, offering a rationale for anti-cancer drug design

  saccharomyces sapiens ihsln genes database phylogenetic gene

• A genome-wide siRNA screen reveals diverse cellular processes and pathways that mediate genome stability.

  PMID 19647519 · PMC2772893 · Molecular cell · 2009 · 8 claims · 6 setups

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  A genome-wide siRNA screen in HeLa cells using γH2AX as a readout identifies genes whose knockdown elevates DNA damage/genome instability

  hela candidate screen genome-wide propidium sirna

• Putting science over supposition in the arena of personalized genomics.

  PMID 18665132 · PMC2531214 · Nature genetics · 2008 · 6 claims · 3 setups

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  There is a rapidly widening gap between gene-disease association discovery and research into the public health/clinical utility of that information.

  adults same tested baseline multiplex telephone-based

• An OMICs-based meta-analysis to support infection state stratification.

  PMID 33560295 · PMC8388022 · Bioinformatics (Oxford, England) · 2021 · 7 claims · 6 setups

  Has reproduction · 44

  Multi-class machine learning models built from cross-platform microarray meta-analysis can distinguish bacterial, viral and no-infection states with high accuracy (best model: 93% bacterial, 89% viral correct).

  blood merged affymetrix-optimized gene feature out-of-sample