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).
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Contribution of oncoproteomics to cancer biomarker discovery.
PMID 17407558 · PMC1852117 · Molecular cancer · 2007 · 6 claims · 8 setups
Oncoproteomic biomarker panels (2-DE/MS-based) show higher sensitivity and specificity than currently used single tumor markers across multiple cancer types (Table 1)
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Identification of biomarkers from mass spectrometry data using a "common" peak approach.
PMID 16869977 · PMC1550264 · BMC bioinformatics · 2006 · 8 claims · 1 setups
"Common" peaks—those exhibited by many subjects—can be identified and used as biomarkers in high-dimensional mass spectrometry data
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A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.
PMID 19828085 · PMC2762074 · BMC bioinformatics · 2009 · 7 claims · 1 setups
A scale-space based unsupervised feature extraction method combined with SVM classification achieves high accuracy in ovarian cancer detection from serum mass spectra.
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Proteomic profiling in ovarian cancer.
PMID 19955909 · PMC7319026 · International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2009 · 8 claims · 6 setups
No validated or cost-efficient screening program exists for ovarian cancer; physical exam, CA125, and transvaginal ultrasound lack sufficient sensitivity/specificity for early-stage detection.
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Glycomics and disease markers.
PMID 19775929 · PMC2788081 · Current opinion in chemical biology · 2009 · 8 claims · 7 setups
Over 70% of all human proteins are glycosylated
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Sample preparation for serum/plasma profiling and biomarker identification by mass spectrometry.
PMID 17166507 · PMC7094463 · Journal of chromatography. A · 2007 · 8 claims · 8 setups
Standardizing sample preparation procedures for serum/plasma profiling is critical for obtaining reliable biomarkers, since slight procedural changes can produce very different protein profiles.
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A European focus on proteomics.
PMID 15128441 · PMC416463 · Genome biology · 2004 · 8 claims · 8 setups
MALDI-MS and ESI-MS are complementary techniques that identify overlapping but distinct subsets of proteins
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Proteomic-based identification of haptoglobin-1 precursor as a novel circulating biomarker of ovarian cancer.
PMID 15199385 · PMC2364749 · British journal of cancer · 2004 · 7 claims · 7 setups
Six serum protein spots (~40 kDa, pI 5.9–6.6) significantly overexpressed in grade 1, 2 and 3 ovarian cancer patients were identified by MALDI-TOFMS and n-ESIQ(q)TOFMS as isoforms of haptoglobin-1 precursor (HAP1)
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Proteomics as a tool for biomarker discovery.
PMID 18057524 · PMC3851415 · Disease markers · 2007 · 8 claims · 7 setups
A useful clinical biomarker must be easily attainable, have adequate sensitivity, have adequate specificity, and lead to patient benefit through intervention
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Diagnostic proteomics: serum proteomic patterns for the detection of early stage cancers.
PMID 15258335 · PMC3851082 · Disease markers · 2003 · 8 claims · 8 setups
Proteomic pattern analysis of serum mass spectra, without identifying the underlying proteins, can distinguish cancer patients from healthy controls with high sensitivity and specificity.
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The cancer secretome: a reservoir of biomarkers.
PMID 18796163 · PMC2562990 · Journal of translational medicine · 2008 · 8 claims · 8 setups
Cancer secretome analysis is a promising reservoir for identifying novel, non-invasive cancer biomarkers, addressing limitations of whole blood/serum proteomics
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Proteomics: characterizing the cogs in the machinery of life.
PMID 14630521 · PMC1241753 · Environmental health perspectives · 2003 · 8 claims · 5 setups
Protein expression patterns in blood serum, detected via SELDI-TOF mass spectrometry and analyzed with a genetic algorithm, can distinguish ovarian cancer patients from healthy individuals with very high sensitivity and specificity.
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On consensus biomarker selection.
PMID 17570864 · PMC1892093 · BMC bioinformatics · 2007 · 7 claims · 2 setups
Four popular feature ranking criteria (t-statistic, mutual information, peak probability contrasts, random forest variable importance) produce different rankings of the same features on the same dataset.