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).

• Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum.

  PMID 16980117 · PMC7159276 · Lancet (London, England) · 2006 · 8 claims · 5 setups

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  An SVM classifier trained on serum proteomic profiles discriminated patients with active tuberculosis from controls with clinically overlapping conditions

  serum computational kda spin-column seldi-tof supervised peptide

• 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

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  A scale-space based unsupervised feature extraction method combined with SVM classification achieves high accuracy in ovarian cancer detection from serum mass spectra.

  serum high-resolution

• 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

• 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

• 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

• Estimation of relevant variables on high-dimensional biological patterns using iterated weighted kernel functions.

  PMID 18509521 · PMC2396875 · PloS one · 2008 · 7 claims · 6 setups

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  wKIERA combines a weighted-kernel discriminant (kernel perceptron) with an iterative stochastic probability estimation-of-distribution algorithm to estimate a relevance distribution over variables

  serum colon glioblastoma synthetic seldi-tof gene computational

• 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

• Bioinformatics methods for learning radiation-induced lung inflammation from heterogeneous retrospective and prospective data.

  PMID 19704920 · PMC2688763 · Journal of biomedicine & biotechnology · 2009 · 8 claims · 3 setups

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  Kernel-based methods (e.g., SVM) can capture nonlinear dose-volume interactions relevant to predicting radiation pneumonitis

  nsclc inoperable blood retrospective prospective 3-way

• SePaCS--a web-based application for classification of seroreactivity profiles.

  PMID 17478503 · PMC1933220 · Nucleic acids research · 2007 · 8 claims · 4 setups

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  SePaCS is a freely available web-based tool that trains and applies multiple classification methods (4 Naive Bayes variants, SVM with RBF kernel, LDA, DLDA) to seroreactivity profiles and outputs results as a summary table plus a detailed PDF report

  blood computational seroreactivity supervised mutual

• 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