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).

• 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

• 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

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  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

  plasma discretized seldi-tof serum logical

• Discovery and identification of potential biomarkers of papillary thyroid carcinoma.

  PMID 19785722 · PMC2761863 · Molecular cancer · 2009 · 8 claims · 7 setups

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  A 3-peak (m/z 9190, 6631, 8697 Da) SVM classification model discriminates PTC from non-cancer controls with high sensitivity and specificity

  serum hplc-purified trypsin-digested crude seldi-tof-ms solid-phase maldi-tof-ms

• Integrated multi-level quality control for proteomic profiling studies using mass spectrometry.

  PMID 19055809 · PMC2657802 · BMC bioinformatics · 2008 · 7 claims · 5 setups

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  QC processes for identifying and removing low-quality spectra are often overlooked in proteomic profiling studies

  serum pooled duplicate full seldi-tof principal technical

• Constructing support vector machine ensembles for cancer classification based on proteomic profiling.

  PMID 16689692 · PMC5173238 · Genomics, proteomics & bioinformatics · 2005 · 7 claims · 4 setups

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  CSVME, built by selecting a subset of base SVMs via SVM-RFE ranking and fusing them with a trained upper-layer SVM, achieves better classification performance than an ensemble of all base SVMs.

  serum computational seldi-tof svm-rfe-based 10-fold

• 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

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  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

  serum seldi seldi-tof-ms chemiluminescence bioinformatic

• 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

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  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.

  blood baseline-corrected 953-dimensional training seldi-tof wavelet ant

• Urinary proteomic profiling for diagnostic bladder cancer biomarkers.

  PMID 19811072 · PMC3422861 · Expert review of proteomics · 2009 · 8 claims · 8 setups

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  Single protein biomarkers (e.g., NMP-22, BTA) suffer from high false-positive rates and none have replaced cystoscopy or cytology for bladder cancer detection.

  urine page gel 2d-dige