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).

• On the analysis of glycomics mass spectrometry data via the regularized area under the ROC curve.

  PMID 18076765 · PMC2211327 · BMC bioinformatics · 2007 · 8 claims · 4 setups

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  The TGDR-AUC algorithm regularizes the empirical AUC by replacing the non-differentiable 0-1 loss with a smooth sigmoid surrogate function and applies constrained threshold gradient descent regularization

  simulated serum preprocessed simulation mass high-resolution

• RADAR: differential analysis of MeRIP-seq data with a random effect model.

  PMID 31870409 · PMC6927177 · Genome biology · 2019 · 8 claims · 6 setups

  Has reproduction · 10

  RADAR is a novel analytical tool for differential methylation analysis of MeRIP-seq data combining gene-level INPUT normalization with a Poisson random effect model.

  simulated fallopian pancreatic liver merip-seq m6a-merip-seq pca

• A novel wavelet-based thresholding method for the pre-processing of mass spectrometry data that accounts for heterogeneous noise.

  PMID 18615428 · PMC2855839 · Proteomics · 2008 · 6 claims · 4 setups

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  Noise in SELDI-TOF/MALDI-TOF mass spectrometry data is heteroscedastic across the m/z range, with larger variance at lower m/z values, contrary to the homogeneous noise assumption of existing wavelet denoising methods.

  serum raw denoised simulated seldi-tof wavelet-based peak

• Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design.

  PMID 34553212 · PMC8458035 · GigaScience · 2021 · 8 claims · 7 setups

  Has reproduction · 87

  Genetic variation–based demultiplexing tools can be effectively deployed on cancer scRNA-seq tissue using a pooled experimental design, achieving high recall at acceptable precision-recall tradeoffs in both high-CNV (HGSOC) and high-SNV (lung adenocarcinoma) cancers, even with extremely high doublet proportions.

  high-grade lung hgsoc healthy single-cell matched doublet

• CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.

  PMID 26961683 · PMC4784276 · Genome medicine · 2016 · 8 claims · 6 setups

  Has reproduction · 87

  CoINcIDE is a methodological framework that discovers replicable patient subtypes (meta-clusters) across multiple datasets by finding consensus across dataset-specific clusterings, requiring no between-dataset transformations.

  breast ovarian simulated gene semi-supervised novo