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).

• Artificial Intelligence Approach in Machine Learning-Based Modeling and Networking of the Coronavirus Pathogenesis Pathway.

  PMID 40699865 · PMC12191508 · Current issues in molecular biology · 2025 · 8 claims · 8 setups

  Has reproduction

  The coronavirus pathogenesis pathway is activated in SARS-CoV-2-infected iPSC-derived cardiac cells and in SARS-CoV/SARS-CoV-2-infected LUAD cells

  ace2-transfected calu-3 luad ipsc-derived ipa sequencing convolutional

• Deep learning from phylogenies to uncover the epidemiological dynamics of outbreaks.

  PMID 35794110 · PMC9258765 · Nature communications · 2022 · 8 claims · 5 setups

  Has reproduction · 94

  Deep learning (FFNN-SS and CNN-CBLV) enables accurate and fast likelihood-free estimation of epidemiological parameters and model selection from phylogenies

  simulated same hiv-1 simulation-based bayesian maximum-likelihood

• Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues.

  PMID 37995291 · PMC10697738 · Bioinformatics (Oxford, England) · 2023 · 8 claims · 8 setups

  Has reproduction · 79

  CLSM6A is a set of CNN-based deep learning models that predict single-nucleotide-resolution m6A RNA modification sites across eight cell lines and three tissues in H. sapiens

  hct116 a549 brain hek293t miclip m6a-clip-seq m6a-seq

• A generic reference defined by consensus peaks for single-cell ATAC-seq data analysis.

  PMID 41663439 · PMC12996591 · Nature communications · 2026 · 7 claims · 7 setups

  Full-text index only

  Aggregating peaks from 624 high-quality bulk ATAC-seq datasets defines ~1.4 million observed consensus peaks (cPeaks) covering ~30% of the genome.

  bulk scatac-seq cnn gm12878 bulk scatac-seq deep

• AMR-GNN: a multi-representation graph neural network framework to enable genomic antimicrobial resistance prediction.

  PMID 41792137 · PMC13087051 · Nature communications · 2026 · 7 claims · 8 setups

  Full-text index only

  AMR-GNN, a graph neural network integrating multiple genomic representations (unitigs, SNPs, FCGR) via low-rank multimodal fusion, improves AMR phenotype prediction in P. aeruginosa compared to single-representation baseline models.

  pseudomonas aeruginosa escherichia coli whole-genome elastic convolutional

• Uncertainty-aware genomic deep learning with knowledge distillation.

  PMID 41523993 · PMC12779563 · NPJ artificial intelligence · 2026 · 7 claims · 6 setups

  Full-text index only

  DEGU distills an ensemble of teacher DNNs into a single student model by jointly predicting the ensemble mean and the variability (epistemic uncertainty) across ensemble predictions.

  drosophila k562 deepstarr starr-seq starr-seq-derived lentimpra base-resolution

• Annotation-free prediction of immunotherapy response in melanoma using single-cell transcriptomic data.

  PMID 41758825 · PMC12948085 · PloS one · 2026 · 8 claims · 6 setups

  Full-text index only

  AI-based predictive models built on unannotated scRNA-seq data (cell-by-gene expression matrices) can classify melanoma patients as ICI responders vs. non-responders

  cd45+ scrna-seq independent scrna-seq single-gene-level pathway-level

• Cross-species prediction reveals chromatin regions with increased accessibility in humans.

  PMID 41984952 · PMC13082337 · Science advances · 2026 · 8 claims · 8 setups

  Full-text index only

  CNNs trained exclusively on human ATAC-seq data achieve cross-species prediction performance in chimpanzees and macaques comparable to species-specific models

  lymphoblastoid prefrontal six chimpanzee bulk single-cell cnn

• Machine and Deep Learning Reveal Sequence Determinants Encoding Bivalent Histone Modifications.

  PMID 41946881 · PMC13057473 · Communications biology · 2026 · 8 claims · 7 setups

  Full-text index only

  Bivalent domains have higher GC content and stronger evolutionary conservation than monovalent regions

  embryonic mesc random bivalent chip-seq rna-seq k-mer-based