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

• CanPredict: a computational tool for predicting cancer-associated missense mutations.

  PMID 17537827 · PMC1933186 · Nucleic acids research · 2007 · 8 claims · 7 setups

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  CanPredict is a web application providing public access to a random forest classifier that combines SIFT, LogR.E-value, and GOSS scores to predict whether a missense mutation is cancer-associated

  missense observed sjoblom refseq cross-validation recurrence comparative

• nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms.

  PMID 15980516 · PMC1160133 · Nucleic acids research · 2005 · 6 claims · 4 setups

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  nsSNPAnalyzer is a web server that predicts whether a query nsSNP is disease-associated or functionally neutral using a Random Forest classifier combining structural and evolutionary information

  curated homologous structure random structural secondary

• Analysis of protein sequence and interaction data for candidate disease gene prediction.

  PMID 17020920 · PMC1636487 · Nucleic acids research · 2006 · 8 claims · 7 setups

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  Combining CPS and CMP using known disease genes as input achieves sensitivity 0.52 and specificity 0.97, reducing candidate lists 13-fold

  ophid biocarta kegg pfam-annotated common benchmarking multiple-interval

• Global distribution of rubella virus genotypes.

  PMID 14720390 · PMC3034328 · Emerging infectious diseases · 2003 · 8 claims · 6 setups

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  Phylogenetic analysis of 103 E1 gene sequences from 17 countries confirms at least two rubella virus genotypes, RGI and RGII

  rubella same phylogenetic genetic virus

• 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

• Multilocus analysis of SNP and metabolic data within a given pathway.

  PMID 16412218 · PMC1382210 · BMC genomics · 2006 · 8 claims · 7 setups

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  The combinatorial partitioning method (CPM) with optimal thresholds can identify SNPs associated with quantitative metabolite levels rather than only categorical traits.

  healthy plasma genomic chi-square combinatorial leave-one-out

• Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients.

  PMID 34421903 · PMC8375662 · Frontiers in immunology · 2021 · 8 claims · 8 setups

  Has reproduction · 71

  TB patients show substantial individual variability in the intensity of hallmark IFN responses, as well as in complement system, metabolic, and other pathway responses.

  blood cynomolgus external gene differential principal

• Speeding disease gene discovery by sequence based candidate prioritization.

  PMID 15766383 · PMC1274252 · BMC bioinformatics · 2005 · 7 claims · 8 setups

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  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.

  ensembl training same hgmd comparative machine tenfold

• Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes.

  PMID 18053250 · PMC2246260 · Genome biology · 2007 · 8 claims · 4 setups

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  Loss-of-function phenotypes in yeast are predictable from a gene's connections in a functional gene network via guilt-by-association.

  saccharomyces guilt-by-association comparison network-guided

• Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.

  PMID 18005451 · PMC2216041 · BMC bioinformatics · 2007 · 8 claims · 5 setups

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  Parepro, an SVM-based method integrating three attribute sets (RD, MI, IE) derived from evolutionary and residue-property information, predicts whether an nsSNP is deleterious or neutral.

  sequences target svm benchmark homology

• 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

• 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

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  Combining high protein-interaction network scores with significant PID-related GO terms identifies novel PID candidate genes

  immunome known protein-interaction gene comparative

• Integrating complex genomic datasets and tumour cell sensitivity profiles to address a 'simple' question: which patients should get this drug?

  PMID 20003409 · PMC2799438 · BMC medicine · 2009 · 8 claims · 5 setups

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  A panel of 48 genomically characterized breast cancer cell lines can model patient tumour heterogeneity to identify biomarkers predicting response to PG-11047

  panel breast 250-gene candidate genome growth pathway

• Species-specific protein sequence and fold optimizations.

  PMID 12487631 · PMC139977 · BMC bioinformatics · 2002 · 7 claims · 7 setups

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  Environmental niche is a significant factor explaining variability in amino acid composition across 100 complete genomes

  predicted mean over orf principal hierarchical domain-based

• Boosting accuracy of automated classification of fluorescence microscope images for location proteomics.

  PMID 15207009 · PMC449699 · BMC bioinformatics · 2004 · 8 claims · 8 setups

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  New classifiers (SVMs, ensembles) and new wavelet-derived (Gabor, Daubechies) features improve recognition of protein subcellular location patterns over the previous neural network approach

  hela automated stepwise training-set-size

• Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy.

  PMID 16984653 · PMC1618409 · BMC bioinformatics · 2006 · 8 claims · 6 setups

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  The proposed feature set outperforms existing published feature sets for predicting effects of amino acid substitutions

  coli bacteriophage lac proteins svm simulated pearson

• Discovering cancer genes by integrating network and functional properties.

  PMID 19765316 · PMC2758898 · BMC medical genomics · 2009 · 8 claims · 6 setups

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  Cancer genes have distinct PPI network topology (higher connectivity, higher clustering coefficient, shorter path length to known cancer genes) compared to non-cancer genes

  genes gene colon ppi pfam term

• A Decentralized Kidney Transplant Biopsy Classifier for Transplant Rejection Developed Using Genes of the Banff-Human Organ Transplant Panel.

  PMID 35619722 · PMC9128066 · Frontiers in immunology · 2022 · 6 claims · 6 setups

  Has reproduction · 90

  A random forest model trained solely on B-HOT panel genes (B-HOT Model) accurately classifies kidney transplant biopsies as NR, ABMR, or TCMR.

  kidney gene combined microarray machine sequential

• Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties.

  PMID 16790052 · PMC1534064 · BMC bioinformatics · 2006 · 8 claims · 7 setups

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  The Sequential Minimal Optimization (SMO) SVM algorithm was the best-performing classifier among 26 WEKA classifiers for predicting catalytic residues

  benchmarking same pirsf pdb supervised wrapper sequence