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).

• 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

• Gene signature discovery and systematic validation across diverse clinical cohorts for TB prognosis and response to treatment.

  PMID 37471455 · PMC10393163 · PLoS computational biology · 2023 · 8 claims · 8 setups

  Has reproduction · 100

  A network-based meta-analysis across studies identifies a common 45-gene signature specific to active TB disease that accounts for cohort/population heterogeneity

  n×m common independent viral blood gene random

• Decision forest analysis of 61 single nucleotide polymorphisms in a case-control study of esophageal cancer; a novel method.

  PMID 16026601 · PMC1637030 · BMC bioinformatics · 2005 · 8 claims · 2 setups

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  DF-SNPs, a novel adaptation of the Decision Forest method, can classify esophageal cancer cases vs. controls based on SNP genotype data with high concordance, sensitivity, and specificity.

  genomic snp high-throughput decision

• Shotgun proteomics and biomarker discovery.

  PMID 12364816 · PMC3851423 · Disease markers · 2002 · 8 claims · 7 setups

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  Shotgun (LC/LC-MS/MS, e.g. MudPIT) proteomic approaches show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range.

  urine yeast cysteine-containing hemoglobin 2d-ge lc-ms imac

• Size matters: just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology.

  PMID 18676414 · PMC2639365 · International journal of epidemiology · 2009 · 7 claims · 2 setups

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  Conventional power calculations for case-control studies disregard analytic complexity (e.g. clinical assessment errors, unmeasured aetiological determinants) and can seriously underestimate true sample size requirements

  simulated simulation-based simulated