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).
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A unified framework for correcting batch effects and integrating multi-omics data.
PMID 41786846 · PMC13079841 · Scientific reports · 2026 · 7 claims · 6 setups
MoDAmix, a four-stage domain adaptation framework (pre-training, single-omics adversarial adaptation, multi-omics adversarial alignment, semi-supervised class alignment), unifies batch correction across multiple omics layers.
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A novel deep learning-driven framework for improving lncRNA comprehensive annotation with LncADeep 2.0.
PMID 41923359 · PMC13090826 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups
LncADeep 2.0 outperforms LncADeep and other existing tools for lncRNA identification on both GENCODE annotated transcripts and independent RNA-seq data
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scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning.
PMID 41507436 · PMC12859067 · Communications biology · 2026 · 7 claims · 7 setups
scXDR outperforms seven methods that transfer drug response information from bulk RNA-seq to single-cell data, across all four evaluated scenarios
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Hi-Compass: a depth-aware deep learning framework for predicting cell-type-specific 3D genome organization from single-cell to spatial resolution.
PMID 41980945 · PMC13250166 · Nature communications · 2026 · 8 claims · 8 setups
Hi-Compass predicts cell-type-specific Hi-C contact maps using only ATAC-seq as cell-type-specific input, plus DNA sequence and a generalized CTCF binding profile