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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Speeding disease gene discovery by sequence based candidate prioritization.
PMID 15766383 · PMC1274252 · BMC bioinformatics · 2005 · 7 claims · 8 setups
Disease genes (OMIM) differ significantly from non-disease genes in sequence-based features including gene/cDNA/protein size, exon number, homolog conservation, secretion signal, 3' UTR length, CpG islands, and distance to nearest gene.
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POCUS: mining genomic sequence annotation to predict disease genes.
PMID 14611661 · PMC329128 · Genome biology · 2003 · 8 claims · 6 setups
Genes predisposing to the same disease tend to share functional annotation IDs (GO/InterPro) more than expected by chance
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Phenotypic categorization of genetic skin diseases reveals new relations between phenotypes, genes and pathways.
PMID 19744994 · PMC2773259 · Bioinformatics (Oxford, England) · 2009 · 8 claims · 5 setups
560 genetic skin diseases can be decomposed into 71 elementary phenotypic features (42 dermatologic, 29 systemic) that combine to represent each disease as a point in a multidimensional phenotype space
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Disease-aging network reveals significant roles of aging genes in connecting genetic diseases.
PMID 19779549 · PMC2739292 · PLoS computational biology · 2009 · 8 claims · 8 setups
Human disease genes are much closer to aging genes in the PPI network than expected by chance
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Discovering cancer genes by integrating network and functional properties.
PMID 19765316 · PMC2758898 · BMC medical genomics · 2009 · 8 claims · 6 setups
Cancer genes have distinct PPI network topology (higher connectivity, higher clustering coefficient, shorter path length to known cancer genes) compared to non-cancer genes
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Integration of text- and data-mining using ontologies successfully selects disease gene candidates.
PMID 15767279 · PMC1065256 · Nucleic acids research · 2005 · 7 claims · 6 setups
Integrating eVOC anatomical ontology-based text-mining of PubMed abstracts with data-mining of gene expression annotation successfully selects and prioritizes candidate disease genes
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Distribution and effects of nonsense polymorphisms in human genes.
PMID 18852891 · PMC2561068 · PloS one · 2008 · 8 claims · 8 setups
Nonsense SNPs occur at a lower density than nonsynonymous SNPs, indicating stronger purifying selection against premature stop codons than amino acid changes.
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The role of positive selection in determining the molecular cause of species differences in disease.
PMID 18837980 · PMC2576240 · BMC evolutionary biology · 2008 · 8 claims · 6 setups
Genes predicted to be under positive selection during human evolution are implicated in diseases (epithelial cancers, schizophrenia, autoimmune diseases, Alzheimer's disease) that differ in prevalence and symptomatology between humans and other mammals
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Commonality of functional annotation: a method for prioritization of candidate genes from genome-wide linkage studies.
PMID 18263617 · PMC2275105 · Nucleic acids research · 2008 · 8 claims · 7 setups
Genes correlated with a common complex trait are more likely to share GO functional annotations than genes not correlated with that trait
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Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.
PMID 16757574 · PMC1475747 · Nucleic acids research · 2006 · 6 claims · 8 setups
Applying seven independent computational disease-gene prioritization methods in concert to 9556 positional candidate genes identifies a prioritized set of likely T2D and obesity candidate genes
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Genome-wide analysis of human disease alleles reveals that their locations are correlated in paralogous proteins.
PMID 18989397 · PMC2565504 · PLoS computational biology · 2008 · 7 claims · 5 setups
The locations of sequence variants are correlated between paralogous human proteins more than expected by chance.
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Correlation of microsynteny conservation and disease gene distribution in mammalian genomes.
PMID 19909546 · PMC2779822 · BMC genomics · 2009 · 7 claims · 8 setups
Density of mouse orthologs of human disease genes correlates with regions of conserved microsynteny in the mouse genome
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Has reproduction
Using random walks to identify cancer-associated modules in expression data.
PMID 24128261 · PMC4015830 · BioData mining · 2013 · 8 claims · 8 setups
Walktrap-GM, a random-walk community detection algorithm adapted with stopping criteria (maximum modularity, maximum size, maximum module score), identifies modules significantly enriched with cancer genes in expression-weighted interaction networks.