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).

• Network-assisted protein identification and data interpretation in shotgun proteomics.

  PMID 19690572 · PMC2736651 · Molecular systems biology · 2009 · 7 claims · 7 setups

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  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.

  yeast organs mammary organ shotgun clique-enrichment microarray

• 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

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  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

  saccharomyces homo bank computational yeast tandem

• Filtering high-throughput protein-protein interaction data using a combination of genomic features.

  PMID 15833142 · PMC1127019 · BMC bioinformatics · 2005 · 8 claims · 8 setups

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  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.

  saccharomyces bank caenorhabditis homo yeast mass naive

• VIRGO: computational prediction of gene functions.

  PMID 16845022 · PMC1538839 · Nucleic acids research · 2006 · 8 claims · 6 setups

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  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

  cerevisiae sapiens leave-one-out gene protein-protein

• 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

• Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network.

  PMID 19728866 · PMC2768980 · Genome biology · 2009 · 6 claims · 6 setups

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  Integrating 16 genomic features (32 sub-features) via a naïve Bayes classifier produces a genome-scale FLN of 21,657 human genes and 22,388,609 weighted links that outperforms any individual data source for inferring functional linkages.

  genome gene omim known naïve linkage disease-centric

• Biocomputing enters its adolescence.

  PMID 15960815 · PMC1175967 · Genome biology · 2005 · 8 claims · 8 setups

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  A 'match augmentation' algorithm efficiently matches structural motifs by prioritizing functionally significant residues, enabling function prediction between evolutionarily unrelated proteins

  bank antibody-antigen yeast genome protein-protein empirical integrative

• Foster thy young: enhanced prediction of orphan genes in assembled genomes.

  PMID 34928390 · PMC9023268 · Nucleic acids research · 2022 · 7 claims · 8 setups

  Has reproduction · 84

  Each of the five gene-prediction pipelines under-predicts orphan genes, with detection as low as 11% under one prediction scenario.

  arabidopsis saccharomyces oryza direct braker maker