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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Multilocus analysis of SNP and metabolic data within a given pathway.
PMID 16412218 · PMC1382210 · BMC genomics · 2006 · 8 claims · 7 setups
The combinatorial partitioning method (CPM) with optimal thresholds can identify SNPs associated with quantitative metabolite levels rather than only categorical traits.
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Chemical genomics: what will it take and who gets to play?
PMID 11423004 · PMC138939 · Genome biology · 2001 · 8 claims · 8 setups
Scaling chemical genetics to a genome-wide 'chemical genomics' requires large, well-funded, multidisciplinary centers that integrate compound libraries, protein resources, automation, and profiling technology, and freely distribute data and reagents.
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Metabolism as a complex genetic trait, a systems biology approach: implications for inborn errors of metabolism and clinical diseases.
PMID 18836848 · PMC4319114 · Journal of inherited metabolic disease · 2008 · 7 claims · 8 setups
Synergistic heterozygosity — cumulative heterozygous mutations at multiple loci in functionally related metabolic pathways — can cause physiologically relevant reduction of pathway flux and disease.
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Shaken not stirred: a global research cocktail served in Hinxton.
PMID 18036269 · PMC2258181 · Genome biology · 2007 · 8 claims · 8 setups
Network-guided reverse genetics using probabilistic functional gene networks (e.g. YeastNet, WormNet) reduces the search space for identifying genes in a given biological process
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Identifying drug effects via pathway alterations using an integer linear programming optimization formulation on phosphoproteomic data.
PMID 19997482 · PMC2776985 · PLoS computational biology · 2009 · 7 claims · 4 setups
An ILP formulation of the Boolean pathway optimization problem fits phosphoproteomic data faster and more efficiently than the previously used genetic algorithm (GA) approach.