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

  Full-text index only

  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

• Application of alternative de novo motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites.

  PMID 34547062 · PMC8408018 · Vavilovskii zhurnal genetiki i selektsii · 2021 · 8 claims · 4 setups

  Has reproduction · 62

  MultiDeNA pipeline combines PWM, diPWM, BaMM and InMoDe models to train, evaluate, threshold, and classify ChIP-seq peaks for TFBS structural heterogeneity

  foxa2 genomic frequency chip-seq novo threshold

• MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.

  PMID 24599324 · PMC3944147 · PloS one · 2014 · 8 claims · 8 setups

  Has reproduction · 29

  MOSAIK is the only aligner that consistently aligns reads from all major sequencing platforms (Illumina, AB SOLiD, Roche 454, Ion Torrent, Pacific Biosciences SMRT) using the same algorithmic approach.

  simulated million coli illumina short-read mapping neural-network

• Predicting FOX gene candidates for oxic nitrogen fixation using multi-omic machine learning and comparative bioinformatics.

  PMID 41764348 · PMC13056922 · Scientific reports · 2026 · 8 claims · 6 setups

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  Random Forest, XGBoost, and logistic regression classifiers can meaningfully differentiate literature-validated FOX genes from conserved non-essential genes, with Random Forest achieving the best ROC-AUC (~0.80)

  anabaena diazotrophic gene-level trained bulk quantitative transcription-start-site-derived