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Showing 1–2 of 2 results
Advanced filters: Author: Sebnem Ece Eksi Clear advanced filters
  • Interpretable machine learning integrating singlecell RNA and ATAC data reveals how biological priors guide cell state classification and regulatory program discovery across diverse tissues and cancer models.

    • Samuel D. Kupp
    • Ian A. VanGordon Jr
    • Çiğdem Ak
    ResearchOpen Access
    Communications Biology
    Volume: 8, P: 1-17
  • High tumour heterogeneity hinders the identification of molecular subtypes in prostate cancer. Here, the authors integrate single-cell chromatin accessibility data with multiplex imaging and reveal distinct chromatin features and transcriptional factor binding signatures in high- and low-grade prostate tumours.

    • Sebnem Ece Eksi
    • Alex Chitsazan
    • Andrew C. Adey
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-14