Advanced search

Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–5 of 5 results
Advanced filters: Author: Haoquan Zhao Clear advanced filters

  • Understanding RNA regulation mechanisms is crucial for developing targeted therapies for diseases and elucidating how cells control gene expression. This study presents a physics-informed machine learning framework to investigate dynamic regulatory mechanisms in RNA complexes, which when applied to the P-TEFb/Tat/TAR system involved in HIV-1 transcriptional activation and the aaRS/tRNA system essential for genetic translation, outperforms existing methods for uncovering latent regulatory networks.

    • Haoquan Liu
    • Yanan Zhu
    • Yunjie Zhao
    ResearchOpen Access
    Communications Physics
    Volume: 9, P: 1-10

  • This study has developed a new method to predict RNA-protein interactions by combining graph neural networks and unsupervised large language models. The model showed superior performances by benchmark tests, especially for previously unseen RNAs and proteins.

    • Haoquan Liu
    • Yiren Jian
    • Yunjie Zhao
    ResearchOpen Access
    Communications Biology
    Volume: 8, P: 1-14

  • hPSCs model of Maturity Onset Diabetes of the Young caused by mutations in the transcription factor HNF1A (HNF1A-MODY), regulates the expression of genes required for the formation of dense-core insulin granules and calcium-dependent insulin secretion, demonstrating a basis to treat HNF1A-MODY patients with sulfonylureas.

    • Bryan J. González
    • Haoquan Zhao
    • Dieter Egli
    ResearchOpen Access
    Communications Biology
    Volume: 5, P: 1-17