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).

• In silico segmentations of lentivirus envelope sequences.

  PMID 17376229 · PMC1847453 · BMC bioinformatics · 2007 · 8 claims · 8 setups

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  C and V regions of lentivirus SU sequences have distinct statistical (oligonucleotide/amino-acid) compositions that HMMs can learn and use to delimit them.

  eiav hiv hmm-based hmm artificial

• Modeling genetic inheritance of copy number variations.

  PMID 18832372 · PMC2588508 · Nucleic acids research · 2008 · 8 claims · 4 setups

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  A joint HMM framework for parents-offspring trios significantly improves CNV call rates and boundary inference accuracy compared to existing methods.

  simulated parent-offspring hapmap hmm-based snp genotype

• A model-based approach to selection of tag SNPs.

  PMID 16776821 · PMC1525207 · BMC bioinformatics · 2006 · 7 claims · 5 setups

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  The Li and Stephens hidden Markov model outperforms other tested models (simple Markov, two-state HMM, HMM-4D, greedy GR-1/GR-2) in description code-length, tag set information content, and prediction of tagged SNPs.

  hapmap encode enr112 tag cross-validated entropy tagged

• snoSeeker: an advanced computational package for screening of guide and orphan snoRNA genes in the human genome.

  PMID 16990247 · PMC1636440 · Nucleic acids research · 2006 · 8 claims · 5 setups

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  snoSeeker (comprising CDseeker and ACAseeker) is a computational package that can screen for both guide and orphan snoRNA genes, unlike prior programs limited to guide snoRNAs

  whole-genome genome computational gene northern

• Local combinational variables: an approach used in DNA-binding helix-turn-helix motif prediction with sequence information.

  PMID 19651875 · PMC2761287 · Nucleic acids research · 2009 · 8 claims · 7 setups

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  The LCV approach predicts HTH motifs with 93.29% accuracy, 93.93% sensitivity and 92.66% specificity using only primary sequence information

  quintessentialset-88 hth same newly lcs svm traditional