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).

• An end-to-end generalizable deep learning framework to comprehensively analyze transcriptional regulation.

  PMID 41922356 · PMC13212934 · Nature communications · 2026 · 8 claims · 7 setups

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  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

  k562 gm12878 imr-90 ro-seq chip-seq functional

• Identification of novel DNA sequence motifs that modulate transcription in T cells.

  PMID 41514212 · PMC12879379 · BMC genomics · 2026 · 8 claims · 8 setups

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  Identified 2,036 novel DNA motifs enriched in regulatory regions of T-cell-specific genes

  t-cell non-t-cell cd4+ sequences rna-seq dnase-seq h3k27ac