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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Biomarkers of lupus nephritis determined by serial urine proteomics.
PMID 18596723 · PMC2614389 · Kidney international · 2008 · 7 claims · 6 setups
SELDI-TOF-MS screening of the LMW urine proteome identifies protein ions that are differentially expressed across phases of the lupus nephritis flare cycle (baseline, pre-flare, flare, post-flare)
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Method of regulatory network that can explore protein regulations for disease classification.
PMID 19962281 · PMC7126395 · Artificial intelligence in medicine · 2010 · 6 claims · 2 setups
A regulatory network (RN) can be constructed as a hopfield-like network, with nodes as biomarkers and directed weighted connections as regulatory relationships, optimized by minimizing an energy function measuring input-output disagreement.
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A novel peak detection approach with chemical noise removal using short-time FFT for prOTOF MS data.
PMID 19681055 · PMC2782493 · Proteomics · 2009 · 8 claims · 2 setups
PDA_stFFT is a novel automatic peak detection method for prOTOF MS data that does not require a priori knowledge of protein masses
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Serum protein profile in systemic-onset juvenile idiopathic arthritis differentiates response versus nonresponse to therapy.
PMID 15987476 · PMC1175022 · Arthritis research & therapy · 2005 · 8 claims · 8 setups
SELDI-TOF MS can differentiate serum protein profiles of active versus well-controlled SJIA
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Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum.
PMID 16980117 · PMC7159276 · Lancet (London, England) · 2006 · 8 claims · 5 setups
An SVM classifier trained on serum proteomic profiles discriminated patients with active tuberculosis from controls with clinically overlapping conditions
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Mining novel biomarkers for prognosis of gastric cancer with serum proteomics.
PMID 19740432 · PMC2753349 · Journal of experimental & clinical cancer research : CR · 2009 · 7 claims · 4 setups
A 5-peak prognosis pattern (4474, 4542, 6443/6643, 4988, 6685 Da) predicts poor vs good prognosis in GC with higher sensitivity/specificity than CEA and TNM stage
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Swarm intelligence based wavelet coefficient feature selection for mass spectral classification: an application to proteomics data.
PMID 19733729 · PMC2748225 · Analytica chimica acta · 2009 · 8 claims · 4 setups
ACA-based wavelet coefficient feature selection can achieve up to 100% classification accuracy on training, validating, and independent testing sets using only 5 selected features.
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Proteomics technologies and challenges.
PMID 17893073 · PMC5054093 · Genomics, proteomics & bioinformatics · 2007 · 8 claims · 8 setups
The proteome reflects the dynamic state of a cell, tissue, or organism more accurately than the genome, so proteomics is expected to yield better disease markers for diagnosis and therapy monitoring.
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Biomarkers that discriminate multiple myeloma patients with or without skeletal involvement detected using SELDI-TOF mass spectrometry and statistical and machine learning tools.
PMID 17124346 · PMC3862287 · Disease markers · 2006 · 8 claims · 5 setups
SELDI-TOF MS serum profiling can discriminate MM patients with vs without skeletal (bone lesion) involvement using peak biomarkers
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A novel wavelet-based thresholding method for the pre-processing of mass spectrometry data that accounts for heterogeneous noise.
PMID 18615428 · PMC2855839 · Proteomics · 2008 · 6 claims · 4 setups
Noise in SELDI-TOF/MALDI-TOF mass spectrometry data is heteroscedastic across the m/z range, with larger variance at lower m/z values, contrary to the homogeneous noise assumption of existing wavelet denoising methods.
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Development of proteomic patterns for detecting lung cancer.
PMID 14757945 · PMC3851077 · Disease markers · 2003 · 8 claims · 3 setups
A decision tree classification algorithm built on three serum protein mass peaks (8122Da, 1452Da, 1610Da) can discriminate lung cancer patients from healthy controls
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Application of serum SELDI proteomic patterns in diagnosis of lung cancer.
PMID 16029516 · PMC1183195 · BMC cancer · 2005 · 6 claims · 2 setups
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
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Preclinical and post-treatment changes in the HCC-associated serum proteome.
PMID 17060939 · PMC2360589 · British journal of cancer · 2006 · 7 claims · 6 setups
SELDI proteomic profiling of serum reveals consistent, statistically significant changes associated with the development of HCC in hepatitis C patients
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Identification of serum biomarkers for colon cancer by proteomic analysis.
PMID 16755300 · PMC2361335 · British journal of cancer · 2006 · 8 claims · 8 setups
Complement C3a des-arg, α1-antitrypsin and transferrin were identified as serum proteins with diagnostic potential for CRC.
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Application of ProteinChip array profiling in serum biomarker discovery for patients suffering from severe acute respiratory syndrome.
PMID 18220240 · PMC7120874 · Methods in molecular biology (Clifton, N.J.) · 2007 · 8 claims · 5 setups
SELDI-TOF-MS ProteinChip array profiling of serum can identify differentially expressed protein biomarkers in SARS-CoV infected patients versus controls.
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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
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.
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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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Detection of venous thromboembolism by proteomic serum biomarkers.
PMID 17579716 · PMC1891085 · PloS one · 2007 · 5 claims · 8 setups
A neural network-based classifier built from direct MALDI-TOF MS serum protein expression profiles can diagnose VTE with sensitivity/specificity that exceeds D-dimer assays
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Logical Analysis of Data (LAD) model for the early diagnosis of acute ischemic stroke.
PMID 18616825 · PMC2492849 · BMC medical informatics and decision making · 2008 · 7 claims · 5 setups
An LAD classification model built from a support-set of 3 peptide peaks can distinguish stroke patients from controls with 75% accuracy on an independent validation set
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Multidimensional proteomics analysis of amniotic fluid to provide insight into the mechanisms of idiopathic preterm birth.
PMID 18431506 · PMC2315798 · PloS one · 2008 · 7 claims · 7 setups
A novel 5-peak SELDI proteomic signature (Q-profile) in the 10-12.5 kDa mass range identifies a subgroup of women at risk for preterm birth without intra-amniotic inflammation or bleeding.