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).

• Exhaustive prediction of disease susceptibility to coding base changes in the human genome.

  PMID 18793467 · PMC2537574 · BMC bioinformatics · 2008 · 8 claims · 7 setups

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  Inter-species conservation is the strongest single predictor of disease-associated coding mutations among the factors tested.

  hgmd refseq aligned svm svm reciprocal inter-species

• 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

• The UCSC genome browser database: update 2007.

  PMID 17142222 · PMC1669757 · Nucleic acids research · 2007 · 8 claims · 8 setups

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  The UCSC Genome Browser Database provides sequence and annotation data for 13 vertebrate and 19 invertebrate species as of September 2006.

  hg17 genome lines xenopus comparative snp linkage

• miRge 2.0 for comprehensive analysis of microRNA sequencing data.

  PMID 30153801 · PMC6112139 · BMC bioinformatics · 2018 · 8 claims · 6 setups

  Has reproduction · 89

  miRge 2.0 introduces a novel SVM-based miRNA detection method using both hairpin structure and isomiR composition, yielding higher specificity for miRNA identification

  pooled colon datasets small a-to-i novel

• 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

• 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

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  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

  pubmed genes same randomly geneseeker evoc disease

• Predicting enhancers in mammalian genomes using supervised hidden Markov models.

  PMID 30917778 · PMC6437899 · BMC bioinformatics · 2019 · 8 claims · 8 setups

  Has reproduction · 70

  eHMM predicts enhancers with high precision and recall comparable to state-of-the-art methods and consistently outperforms them in accuracy and resolution

  esc atac-seq chip-seq cage