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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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
Cellular response to a signal is assumed to involve only specific TRN modules (conditionally active subnetworks) rather than the entire network, providing quantitative tractability
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Has reproduction · 100
Gene co-expression network analysis in human spinal cord highlights mechanisms underlying amyotrophic lateral sclerosis susceptibility.
PMID 33707641 · PMC7970949 · Scientific reports · 2021 · 8 claims · 8 setups
WGCNA on control human cervical spinal cord RNA-seq identifies 13 co-expression modules (SC.M1-M13), each representing distinct biological processes or cell types.
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Systems biology of gene regulation fulfills its promise.
PMID 16719937 · PMC1779525 · Genome biology · 2006 · 8 claims · 8 setups
Suz12, a Polycomb Group complex component, has DNA targets identifiable by ChIP-chip and can silence large genomic regions in a cell-type-specific manner.
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Biocomputing enters its adolescence.
PMID 15960815 · PMC1175967 · Genome biology · 2005 · 8 claims · 8 setups
A 'match augmentation' algorithm efficiently matches structural motifs by prioritizing functionally significant residues, enabling function prediction between evolutionarily unrelated proteins
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Exploration of the omics evidence landscape: adding qualitative labels to predicted protein-protein interactions.
PMID 17880677 · PMC2375035 · Genome biology · 2007 · 7 claims · 8 setups
Combining pairs of omics evidence types into two-dimensional 'evidence landscapes' allows regions to be identified that specifically and purely predict either physical or metabolic protein interactions