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Peer-reviewedCC BY-NCCell genomics

Deep learning uncovers hidden power of low-affinity motifs.

  • Grace Bower1
  • Evgeny Z Kvon2
  1. 1Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA.
  2. 2Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA; Department of Systems Biology, University of California, Irvine, Irvine, CA, USA. Electronic address: [email protected].
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Abstract

Low-affinity transcription factor binding sites are functionally important but difficult to map and mechanistically poorly understood. In this issue of Cell Genomics, Weilert et al. leverage sequence-to-function deep learning models to systematically map low-affinity pioneer factor binding sites in mouse embryonic stem cells and reveal how these sites contribute to chromatin opening through soft-syntax nucleosomal cooperativity.

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Cite

BibTeXRIS
BibTeX
@article{bower2026deep,
  title = {{Deep learning uncovers hidden power of low-affinity motifs.}},
  author = {Grace Bower and Evgeny Z Kvon},
  journal = {Cell genomics},
  year = {2026},
  month = oct,
  doi = {10.1016/j.xgen.2026.101392},
  url = {https://europepmc.org/article/MED/42874569},
  note = {CC BY-NC},
}
RIS
TY  - JOUR
TI  - Deep learning uncovers hidden power of low-affinity motifs.
AU  - Grace Bower
AU  - Evgeny Z Kvon
PY  - 2026
DA  - 2026/10/01
JO  - Cell genomics
DO  - 10.1016/j.xgen.2026.101392
UR  - https://europepmc.org/article/MED/42874569
AB  - Low-affinity transcription factor binding sites are functionally important but difficult to map and mechanistically poorly understood. In this issue of Cell Genomics, Weilert et al. leverage sequence-to-function deep learning models to systematically map low-affinity pioneer factor binding sites in mouse embryonic stem cells and reveal how these sites contribute to chromatin opening through soft-syntax nucleosomal cooperativity.
SN  - 2666-979X
ER  -