DNAmBERT, a Transformer-based deep learning framework designed to jointly model DNA sequence context and read-level methylation haplotype structure from cfDNA methylation sequencing data, indicates that integrated sequence–haplotype representation learning provides an accurate and scalable approach for cfDNA-based mult...
Maryam Yassi, Mark Ezegbogu, E. Rodger et al.· Briefings in Bioinformatics· 0 citations
One of the first integrated genomic, epigenomic, and transcriptomic liquid biopsy datasets for NSCLC in New Zealand is generated, expected to support the development of sensitive, accessible, and equitable blood-based biomarkers for NSCLC detection and treatment monitoring while also contributing to improved precision...
Rajiv Kumar, Safia May Farry, Mark Ezegbogu et al.· JMIR Research Protocols· 0 citations
This review synthesizes current advances in CRISPR-based DNA methylation editing for cancer epigenomics, critically evaluates key challenges, including off-target activity, context-dependent outcomes, delivery and durability, and outlines future directions integrating locus-specific editing with multi-omics profiling,...
Negar Sadeghi, E. Rodger, Aniruddha Chatterjee· Cellular and Molecular Life...· 0 citations
The molecular landscape of prostate cancer is discussed, before providing a detailed overview of the molecular approaches available for early detection and prognostication and highlighting areas of future research.
A. Yee, Jim Smith, Rajiv Kumar et al.· Cancer Metastasis Review· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
