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).

• Genomic data sampling and its effect on classification performance assessment.

  PMID 12553886 · PMC149349 · BMC bioinformatics · 2003 · 8 claims · 3 setups

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  Cross-validation, leave-one-out, and bootstrap are designed to reduce bias and variance in accuracy estimation from small samples.

  leukemia srbct splice-junction supervised

• 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

• Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach.

  PMID 19801557 · PMC2780952 · DNA research : an international journal for rapid publication of reports on genes and genomes · 2009 · 6 claims · 3 setups

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  An SVM trained on 69 binary features of known PID genes can accurately classify PID vs non-PID genes and predict novel candidate PID genes

  genome training svm support leave-one-out sensitivity

• Mining expressed sequence tags identifies cancer markers of clinical interest.

  PMID 17078886 · PMC1635568 · BMC bioinformatics · 2006 · 8 claims · 6 setups

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  An EST-mining approach (Fisher Exact Test on tumor vs. non-tumor library hit counts) identifies differentially expressed transcripts with an estimated false discovery rate below 22% when human and mouse screens are combined.

  dbest cancer gene est human-mouse leave-one-out

• 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

• Bayesian prediction of microbial oxygen requirement.

  PMID 26913185 · PMC4743139 · F1000Research · 2013 · 7 claims · 8 setups

  Has reproduction · 76

  A naive Bayesian classifier based on presence/absence of class-associated Pfam-A domains can distinguish three oxygen requirement classes (aerobe, anaerobe, facultative anaerobe) from genome sequence, unlike prior studies that only made pairwise distinctions.

  bacterial selected predicted pfam-a genome gene domain

• 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