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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An end-to-end generalizable deep learning framework to comprehensively analyze transcriptional regulation.
PMID 41922356 · PMC13212934 · Nature communications · 2026 · 8 claims · 7 setups
BioSeq2Seq is a transformer-based deep learning framework that predicts genome-wide transcriptional regulatory profiles at 128-bp resolution by jointly using RO-seq data and DNA sequence as tri-modal input
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Complete genome of Phenylobacterium zucineum--a novel facultative intracellular bacterium isolated from human erythroleukemia cell line K562.
PMID 18700039 · PMC2529317 · BMC genomics · 2008 · 8 claims · 6 setups
Complete genome of P. zucineum HLK1T consists of a 3,996,255 bp circular chromosome and a 382,976 bp circular plasmid encoding 3,861 proteins, 42 tRNAs, and one 16S-23S-5S rRNA operon
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The 3D genomics of lampbrush chromosomes highlights the role of active transcription in chromatin organization.
PMID 41978268 · PMC13076225 · Nucleic acids research · 2026 · 8 claims · 8 setups
Single-nucleus Hi-C reveals CTCF-independent contact domains with stable boundaries defined by convergently oriented transcription units (TUs)
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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