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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Sys-BodyFluid: a systematical database for human body fluid proteome research.
PMID 18978022 · PMC2686600 · Nucleic acids research · 2009 · 6 claims · 4 setups
Sys-BodyFluid is a web-based database integrating proteomic data from 11 human body fluids (plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, milk, amniotic fluid), containing over 10,000 proteins
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Gene Prospector: an evidence gateway for evaluating potential susceptibility genes and interacting risk factors for human diseases.
PMID 19063745 · PMC2613935 · BMC bioinformatics · 2008 · 8 claims · 5 setups
Gene Prospector is a Web-based application that selects and prioritizes potential disease-related genes using a curated, updated literature database of genetic association studies
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Sequence similarity network reveals common ancestry of multidomain proteins.
PMID 18475320 · PMC2377100 · PLoS computational biology · 2008 · 8 claims · 6 setups
Traditional homology definitions do not capture multidomain evolution; the authors extend the definition to include domain insertion via a common ancestral locus model.
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G2Cdb: the Genes to Cognition database.
PMID 18984621 · PMC2686544 · Nucleic acids research · 2009 · 7 claims · 7 setups
G2Cdb integrates experimentally validated synapse proteome datasets with mouse/human genomic annotation, phenotype, and human disease data in a gene-centric database.
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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.