Ghamdan Al‐Eryani

This paper introduces a high-throughput single-cell RNA isoform sequencing method using sequencing-by-expansion (SBX) and the CUDLL algorithm, achieving high accuracy and enabling isoform-level analysis across cell types.

This study uses single-cell RNA-sequencing and spatial transcriptomics to analyze epithelial and fibroblast states in hormone therapy-naive prostate cancer, identifying novel phenotypes and molecular perturbations.

The paper introduces LRAA, a framework for accurate isoform discovery and quantification in long-read RNA-seq data, outperforming existing methods across multiple benchmarks.

The paper evaluates and optimizes single-cell RNA isoform sequencing by analyzing artifacts from three platforms and introducing methods to reduce their impact.

The paper traces the evolution of autoantibodies in HCV-CV patients, revealing convergent somatic mutations and compromised solubility in pathogenic B cells.

This study introduces a method to generate high-quality single-nucleus transcriptomic data from FFPE samples using recent single-cell genomic technology.

This paper introduces RAGE-seq, a method combining long-read and short-read sequencing to analyze lymphocyte clonal and transcriptional features in breast cancer tissues.