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).

• 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

  Full-text index only

  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

• scSAMAC: saliency-adjusted masking induced attention contrastive learning for single-cell clustering.

  PMID 40131310 · PMC11934584 · Briefings in bioinformatics · 2025 · 8 claims · 1 setups

  Has reproduction · 85

  scSAMAC integrates contrastive learning and negative binomial (NB) losses into a VAE, extracting features via contrastive unit similarity while preserving intrinsic data characteristics to enhance robustness and generalization in clustering.

  scrna-seq scrna-seq

• Biocomputing enters its adolescence.

  PMID 15960815 · PMC1175967 · Genome biology · 2005 · 8 claims · 8 setups

  Full-text index only

  A 'match augmentation' algorithm efficiently matches structural motifs by prioritizing functionally significant residues, enabling function prediction between evolutionarily unrelated proteins

  bank antibody-antigen yeast genome protein-protein empirical integrative

• PrimerStation: a highly specific multiplex genomic PCR primer design server for the human genome.

  PMID 16845094 · PMC1538814 · Nucleic acids research · 2006 · 7 claims · 2 setups

  Full-text index only

  Selecting primers using the stringent hybridization ratio (requiring an 'executable temperature' where target hybridization ratio >0.99 and off-target ratio <0.05) yields more specific genomic primers than the conventional melting-temperature-based approach, which only guarantees >0.5 vs <0.5

  chrx entire multiplex computational

• Seeded Bayesian Networks: constructing genetic networks from microarray data.

  PMID 18601736 · PMC2474592 · BMC systems biology · 2008 · 8 claims · 4 setups

  Full-text index only

  Seeding Bayesian Network analysis with prior networks derived from literature and/or PPI data improves recovery of known gene-gene interactions compared to BN analysis without a seed

  leukemia interactome pubmed-indexed computational microarray yeast literature