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).

• Evolutionary cores of domain co-occurrence networks.

  PMID 15788102 · PMC1079808 · BMC evolutionary biology · 2005 · 8 claims · 4 setups

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  The innermost (globally central) cores of protein domain co-occurrence networks gradually grow in size with increasing evolutionary/developmental complexity of the organism.

  cerevisiae domain weighted comparative

• Organization of physical interactomes as uncovered by network schemas.

  PMID 18949022 · PMC2561054 · PLoS computational biology · 2008 · 7 claims · 5 setups

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  A computational procedure can systematically identify 'emergent' network schemas that are both recurrent and over-represented relative to randomized networks preserving lower-order subschema distributions

  cerevisiae sapiens uncharacterized network cross-species functional

• Bayesian prediction of microbial oxygen requirement.

  PMID 26913185 · PMC4743139 · F1000Research · 2013 · 7 claims · 8 setups

  Has reproduction · 76

  A naive Bayesian classifier based on presence/absence of class-associated Pfam-A domains can distinguish three oxygen requirement classes (aerobe, anaerobe, facultative anaerobe) from genome sequence, unlike prior studies that only made pairwise distinctions.

  bacterial selected predicted pfam-a genome gene domain

• Prioritization of candidate cancer genes--an aid to oncogenomic studies.

  PMID 18710882 · PMC2566894 · Nucleic acids research · 2008 · 8 claims · 8 setups

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  Computational classifiers using combinations of protein conservation, gene structure, protein domains, protein interactions, and regulatory data can distinguish known cancer genes (CD/CR) from unlabelled human genes

  genes cancer interpro interactome averaged cross-validation domain

• Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information.

  PMID 15941473 · PMC1164402 · BMC bioinformatics · 2005 · 8 claims · 5 setups

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  A combined linguistic+statistical+rule-based method achieves precision 0.61 and recall 0.97 (f=0.74) detecting yeast protein-protein interactions across 12,300 Medline abstracts.

  yeast yeast-related interaction random dictionary-based manual graph