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Showing 1–5 of 5 results
Advanced filters: Author: Shushan Toneyan Clear advanced filters

  • Recent developments in deep learning have allowed for a leap in computational analysis of epigenomic data, but a fair comparison of different architectures is challenging. Toneyan et al. use GOPHER, their new framework for model evaluation and comparison, to perform a comprehensive analysis, exploring modelling choices of deep learning for epigenomic profiles.

    • Shushan Toneyan
    • Ziqi Tang
    • Peter K. Koo
    Research
    Nature Machine Intelligence
    Volume: 4, P: 1088-1100

  • Transcription factors (TFs) represent an emerging class of therapeutic targets in oncology. Here, the authors develop Epiregulon, a computational method that constructs gene regulatory networks from ChIP-seq, ATAC-seq and RNA-seq data for accurate prediction of TF activity at the single-cell level, thereby facilitating the discovery of therapeutics targeting TFs.

    • Tomasz Włodarczyk
    • Aaron Lun
    • Xiaosai Yao
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-19

  • CREME is an extensible computational tool for investigating cis-regulation via in silico perturbations of neural network-based DNA sequence models such as Enformer, identifying complex interactions between a gene’s regulatory elements.

    • Shushan Toneyan
    • Peter K. Koo
    Research
    Nature Genetics
    Volume: 56, P: 2517-2527

  • Deep learning shows promise for predicting gene expression levels from DNA sequences. However, recent studies show that current state-of-the-art models struggle to accurately characterize expression variation from personal genomes, limiting their usefulness in personalized medicine.

    • Ziqi Tang
    • Shushan Toneyan
    • Peter K. Koo
    News & Views
    Nature Genetics
    Volume: 55, P: 2021-2022

  • Independent but complementary studies from Vakoc and Stegmaier identify and characterize a role for ETV6 in counteracting the transcriptional activity of EWS-FLI1 during Ewing sarcoma development, which may be targeted for therapeutic benefits.

    • Yuan Gao
    • Xue-Yan He
    • Christopher R. Vakoc
    Research
    Nature Cell Biology
    Volume: 25, P: 298-308