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).

• 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

• Integration of text- and data-mining using ontologies successfully selects disease gene candidates.

  PMID 15767279 · PMC1065256 · Nucleic acids research · 2005 · 7 claims · 6 setups

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  Integrating eVOC anatomical ontology-based text-mining of PubMed abstracts with data-mining of gene expression annotation successfully selects and prioritizes candidate disease genes

  biomedical refseq training independent text-mining data-mining candidate

• JIGSAW, GeneZilla, and GlimmerHMM: puzzling out the features of human genes in the ENCODE regions.

  PMID 16925843 · PMC1810558 · Genome biology · 2006 · 8 claims · 4 setups

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  Adding model states for specific biological features (signal peptides, CpG islands, etc.) to non-comparative GHMM gene finders did little or nothing to enhance predictive accuracy, sometimes reducing it.

  encode genes invertebrate initio comparative training

• A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data.

  PMID 19923232 · PMC2817484 · Nucleic acids research · 2010 · 8 claims · 7 setups

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  A Perl-based pipeline that BLASTs/BLATs Illumina probe sequences against genomes and transcript databases (RefSeq, UCSC Known Genes, UniGene/GenBank, Ensembl) can classify probes by quality grade (Perfect/Good/Bad/No match) and is applicable across 8 BeadArray platforms and other array types

  maqc hepatocytes japanese illeum microarray dasl sequence

• 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

• Comprehensive benchmarking of large language models for RNA secondary structure prediction.

  PMID 40205851 · PMC11982019 · Briefings in bioinformatics · 2025 · 7 claims · 4 setups

  Has reproduction · 88

  Existing RNA-LLMs had not previously been evaluated for secondary structure prediction in a unified, fair experimental setup with the same datasets and prediction model.

  archiveii bprna large-scale secondary cross-family self-supervised