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).

• Detecting transcriptionally active regions using genomic tiling arrays.

  PMID 16859498 · PMC1779562 · Genome biology · 2006 · 8 claims · 4 setups

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  A non-parametric method (TranscriptionDetector) integrates single-channel p-values from multiple replicate arrays into a multi-channel p-value (MCPV) to identify transcribed probed loci without assumptions about intensity distributions.

  anopheles chromosomes simulated genomic high-density sequence-based

• Analysis of sequence conservation at nucleotide resolution.

  PMID 18166073 · PMC2230682 · PLoS computational biology · 2007 · 8 claims · 4 setups

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  SCONE (Sequence CONservation Evaluation) is a novel method that estimates evolutionary rate and a neutrality p-value for individual nucleotide positions in a multiple sequence alignment.

  encode population comparative snp functional

• Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms.

  PMID 15784611 · PMC1069129 · Nucleic acids research · 2005 · 7 claims · 8 setups

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  Position-specific phylogenetic features describing evolutionary conservation at a site (e.g. SIFT score, normalized site entropy, residue frequency change) are the best individual discriminators of disease-causing versus neutral GPCR mutations.

  dbsnp gpcr transmembrane sequence six-frame sift logistic

• Large-scale discovery of insertion hotspots and preferential integration sites of human transposed elements.

  PMID 20008508 · PMC2836564 · Nucleic acids research · 2010 · 8 claims · 6 setups

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  Most TEs insert within specific 'hotspots' along the targeted TE rather than uniformly.

  genome sequences unique nested chi-square position-specific

• Prodepth: predict residue depth by support vector regression approach from protein sequences only.

  PMID 19759917 · PMC2742725 · PloS one · 2009 · 8 claims · 8 setups

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  Residue depth can be reliably predicted solely from protein primary sequence using support vector regression on sequence-derived features.

  structure sequences sequence residue dssp psi-blast