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).

• Randomised trial of a decision aid and its timing for women being tested for a BRCA1/2 mutation.

  PMID 14735173 · PMC2410151 · British journal of cancer · 2004 · 6 claims · 3 setups

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  The DA had no impact on well-being (anxiety, depression, cancer-related distress, general health)

  women brca1 same randomised comparative validated

• Application of serum SELDI proteomic patterns in diagnosis of lung cancer.

  PMID 16029516 · PMC1183195 · BMC cancer · 2005 · 6 claims · 2 setups

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  A five-protein-peak SELDI decision-tree pattern (11493, 6429, 8245, 5335, 2538 Da) distinguishes lung cancer sera from healthy control sera with relatively high sensitivity and specificity

  serum seldi-tof-ms electrochemiluminescent

• Peptide bioinformatics: peptide classification using peptide machines.

  PMID 19065810 · PMC7122642 · Methods in molecular biology (Clifton, N.J.) · 2008 · 8 claims · 4 setups

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  The bio-basis function, which converts peptides into numerical vectors using nongapped pairwise homology alignment scores against indicator peptides, can statistically quantify peptide similarity for classification.

  illustrative query generic synthetic bio-basis orthogonal hyperplane

• Development of proteomic patterns for detecting lung cancer.

  PMID 14757945 · PMC3851077 · Disease markers · 2003 · 8 claims · 3 setups

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  A decision tree classification algorithm built on three serum protein mass peaks (8122Da, 1452Da, 1610Da) can discriminate lung cancer patients from healthy controls

  serum pooled seldi-tof-ms decision reproducibility

• 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

• Serum diagnosis of diffuse large B-cell lymphomas and further identification of response to therapy using SELDI-TOF-MS and tree analysis patterning.

  PMID 18163913 · PMC2242801 · BMC cancer · 2007 · 8 claims · 8 setups

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  SELDI-TOF-MS serum proteomic patterns analyzed by decision tree classification (Biomarker Pattern Software) can discriminate DLBCL patients from healthy controls with high sensitivity and specificity.

  serum seldi dlbcl pooled seldi-tof-ms proteinchip decision

• Integrated analysis of genetic and proteomic data identifies biomarkers associated with adverse events following smallpox vaccination.

  PMID 18923431 · PMC2692715 · Genes and immunity · 2009 · 7 claims · 6 setups

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  A two-stage strategy (Random Forest filtering followed by decision tree modeling) can integrate categorical genetic and continuous proteomic data to identify biomarkers of AE risk

  ebv-transformed serum combined rf-filtered snp serum random

• One-pot shotgun quantitative mass spectrometry characterization of histones.

  PMID 19764812 · PMC2798817 · Journal of proteome research · 2009 · 8 claims · 8 setups

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  One-pot propionylation and trypsin digestion of unfractionated bulk histones enables quantitative Bottom Up MS characterization of histone PTMs without prior off-line HPLC or SDS-PAGE purification

  hela wild-type set2δ yeast bottom rp-hplc one-pot

• 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

• In silico analysis of missense substitutions using sequence-alignment based methods.

  PMID 18951440 · PMC3431198 · Human mutation · 2008 · 8 claims · 7 setups

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  Carefully validated PMSA-based computational algorithms can achieve predictive values of ~75-95% for classifying missense substitutions as pathogenic or neutral.

  clinically sequence curated deep blosum62 sift align-gvgd

• Towards precise classification of cancers based on robust gene functional expression profiles.

  PMID 15774002 · PMC1274255 · BMC bioinformatics · 2005 · 6 claims · 7 setups

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  Functional expression profiles (FEPs) achieve comparable or better classification performance than conventional gene expression profiles (GEPs) across four public microarray datasets

  nci60 lymphoma fep go-annotated cdna recursive hypergeometric

• 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

• Application of machine learning in SNP discovery.

  PMID 16398931 · PMC1955739 · BMC bioinformatics · 2006 · 8 claims · 6 setups

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  PolyBayes produces high false-positive SNP predictions even with stringent parameters

  diverse soybean candidate same sts polybayes polyphred

• Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature.

  PMID 35143511 · PMC8830616 · PloS one · 2022 · 8 claims · 6 setups

  Has reproduction · 48

  A hybrid signature combining the Nottingham Prognostic Index with SIS-selected gene expressions can be built in a data-driven fashion (NPI treated as a gene expression during feature selection).

  metabric scan-b gene rna-seq feature

• Policy implications of genetic information on regulation under the Clean Air Act: the case of particulate matter and asthmatics.

  PMID 16507451 · PMC1392222 · Environmental health perspectives · 2006 · 8 claims · 4 setups

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  The Clean Air Act mandates protection of sensitive subpopulations, including asthmatics, from air pollution health effects, creating an opening for genetic susceptibility data in regulation.

  u.s epa asthma asthmatic statutory regulatory literature

• Ab initio identification of human microRNAs based on structure motifs.

  PMID 18088431 · PMC2238772 · BMC bioinformatics · 2007 · 8 claims · 7 setups

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  MiRPred predicts miRNA precursors ab initio using only predicted secondary structure motifs, ignoring nucleotide sequence

  genome mirna hairpins chromosome secondary linear five-fold

• MALDI profiling of human lung cancer subtypes.

  PMID 19890392 · PMC2767501 · PloS one · 2009 · 8 claims · 8 setups

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  PIMAC/MALDI-TOF peptide profiles combined with classification models can distinguish normal lung from tumor and differentiate NSCLC histological subtypes

  lung tryptic peak ffpe maldi-tof parallel stepwise

• Limitations in SELDI-TOF MS whole serum proteomic profiling with IMAC surface to specifically detect colorectal cancer.

  PMID 19689818 · PMC2743709 · BMC cancer · 2009 · 7 claims · 3 setups

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  The previously reported classifier (m/z 8,132 and 4,002) failed to discriminate CRC patients from healthy volunteers in this independent validation cohort

  serum pooled seldi-tof comparative decision

• Combining evidence of preferential gene-tissue relationships from multiple sources.

  PMID 23950964 · PMC3741196 · PloS one · 2013 · 8 claims · 8 setups

  Has reproduction · 53

  A high-level integration approach combining three methods across four human microarray datasets, merged by consensus voting and a rule-based inner/total score, predicts preferentially expressed genes while reducing method- and study-specific bias.

  normal four microarray genes microarray computational bayes