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).

• scMILD: Single-cell multiple instance learning for sample classification and associated subpopulation discovery.

  PMID 41907409 · PMC13019583 · iScience · 2026 · 8 claims · 8 setups

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  scMILD identifies condition-associated cells using only sample-level labels via a dual-branch MIL architecture with a shared encoder

  simulated lupus covid-19 ulcerative simulated mixture scrna-seq

• multiDEGGs: Single or Multiomic Differential Network Analysis for Biomarker Discovery and Feature Engineering for Predictive Modeling.

  PMID 41993882 · PMC13082464 · Computational and structural biotechnology journal · 2026 · 8 claims · 3 setups

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  multiDEGGs is a CRAN R package enabling differential network analysis in single or multiomic scenarios by identifying differentially expressed gene-gene pairs rather than single differentially expressed genes

  synthetic synovial eight simulated bulk machine

• 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 the effect of CRISPR-Cas9-based epigenome editing.

  PMID 41524535 · PMC12795505 · eLife · 2026 · 8 claims · 6 setups

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  Machine learning (CNN and ridge regression) models trained on histone PTM ChIP-seq and RNA-seq data from 13 ENCODE cell types accurately predict endogenous gene expression, with transcriptome-wide correlations of ~0.70-0.79 for most cell types

  hek293t k562 computational chip-seq rna-seq mnase-seq