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).

• Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning.

  PMID 19756158 · PMC2742196 · PLoS computational biology · 2009 · 8 claims · 4 setups

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  MIP active learning is a novel active learning method that preferentially seeks informative Positive (functionally active) examples rather than only maximizing classifier accuracy.

  engineered p53 computational yeast-based regional homology

• Vertebrate gene finding from multiple-species alignments using a two-level strategy.

  PMID 16925840 · PMC1810555 · Genome biology · 2006 · 8 claims · 5 setups

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  DOGFISH cleanly separates a multi-species alignment classifier (RVM cascade) from an HMM-based structure predictor, avoiding tight coupling of alignment complexity with HMM formalism

  genomic encode entire chromosome multi-species hmm-based classifier

• Ab initio identification of human microRNAs based on structure motifs.

  PMID 18088431 · PMC2238772 · BMC bioinformatics · 2007 · 8 claims · 7 setups

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  MiRPred predicts miRNA precursors ab initio using only predicted secondary structure motifs, ignoring nucleotide sequence

  genome mirna hairpins chromosome secondary linear five-fold

• CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction.

  PMID 18096039 · PMC2246271 · Genome biology · 2007 · 8 claims · 5 setups

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  CONTRAST predicts exact coding region structures for 65% more human genes than the previous state-of-the-art de novo predictor (N-SCAN)

  genome sequence drosophila novo gene coding

• 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

• High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer.

  PMID 17925008 · PMC2246289 · Genome biology · 2007 · 7 claims · 8 setups

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  A novel subtype of high-grade ER-negative breast cancer exists, characterized by a low genomic instability index (GII)

  breast computational array-cgh gene bac