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).

• 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

• 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