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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InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale.
PMID 17868464 · PMC2375030 · Genome biology · 2007 · 8 claims · 8 setups
InSite predicts protein-pair-specific binding motifs ('Motif M on protein A binds to protein B') by integrating heterogeneous PPI and motif-motif interaction evidence within a Bayesian network trained by EM
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VIRGO: computational prediction of gene functions.
PMID 16845022 · PMC1538839 · Nucleic acids research · 2006 · 8 claims · 6 setups
VIRGO constructs a functional linkage network (FLN) from gene expression and molecular interaction data, labels genes with GO annotations, and propagates these labels to predict functions of unlabelled genes
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Identification of candidate disease genes by integrating Gene Ontologies and protein-interaction networks: case study of primary immunodeficiencies.
PMID 19073697 · PMC2632920 · Nucleic acids research · 2009 · 8 claims · 5 setups
Combining high protein-interaction network scores with significant PID-related GO terms identifies novel PID candidate genes
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Analysis of protein sequence and interaction data for candidate disease gene prediction.
PMID 17020920 · PMC1636487 · Nucleic acids research · 2006 · 8 claims · 7 setups
Combining CPS and CMP using known disease genes as input achieves sensitivity 0.52 and specificity 0.97, reducing candidate lists 13-fold
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Filtering high-throughput protein-protein interaction data using a combination of genomic features.
PMID 15833142 · PMC1127019 · BMC bioinformatics · 2005 · 8 claims · 8 setups
A combination of three genomic features (interacting Pfam domains, GO annotations, sequence homology) using naive Bayesian networks predicts true protein-protein interactions with high sensitivity and good specificity.
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Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes.
PMID 18053250 · PMC2246260 · Genome biology · 2007 · 8 claims · 4 setups
Loss-of-function phenotypes in yeast are predictable from a gene's connections in a functional gene network via guilt-by-association.
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Prioritization of candidate cancer genes--an aid to oncogenomic studies.
PMID 18710882 · PMC2566894 · Nucleic acids research · 2008 · 8 claims · 8 setups
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
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Network-assisted protein identification and data interpretation in shotgun proteomics.
PMID 19690572 · PMC2736651 · Molecular systems biology · 2009 · 7 claims · 7 setups
Confidently identified proteins in a sample form tightly connected sub-networks in the protein interaction network, with significantly higher clustering coefficients than random or topology-matched random sub-networks.
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PlasmoDraft: a database of Plasmodium falciparum gene function predictions based on postgenomic data.
PMID 18925948 · PMC2605471 · BMC bioinformatics · 2008 · 8 claims · 4 setups
Gonna, a supervised k-nearest-neighbor Guilt-By-Association predictor, proposes GO annotations for a gene based on similarity of its transcriptome, proteome, or interactome profile to genes already annotated by GeneDB
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The HIV positive selection mutation database.
PMID 17108357 · PMC1669717 · Nucleic acids research · 2007 · 8 claims · 5 setups
The database provides codon-level Ka/Ks selection pressure maps for HIV protease and the first 381 codons of RT, built from a novel ~50,000-sample clinical dataset.
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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