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).

• 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

• 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

• 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

• 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

• 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

• Diagnostic proteomics: serum proteomic patterns for the detection of early stage cancers.

  PMID 15258335 · PMC3851082 · Disease markers · 2003 · 8 claims · 8 setups

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  Proteomic pattern analysis of serum mass spectra, without identifying the underlying proteins, can distinguish cancer patients from healthy controls with high sensitivity and specificity.

  serum frozen ig-depleted clinical seldi-tof maldi lc-ms

• 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

• 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