Lydia Liu

Metapipeline-DNA automates comprehensive analysis of DNA sequencing data from raw reads to visualization, supporting germline and somatic genomic features.

This paper uses N-glycoproteomics to analyze patient-derived xenografts, identifies FAT2 as a therapeutic target for head and neck cancers, and validates its role in tumor growth and CAR T cell activity.

moPepGen identifies non-canonical peptides from genetic and transcriptomic data across species and technologies by generating them in linear time.

The paper quantifies secreted and extracellular vesicle (EV) urinary proteomes in men with and without prostate cancer, showing their stability and utility in distinguishing malignant from benign lesions.

This study evaluates how different random seeds affect subclonal reconstruction algorithms in cancer genomics, finding significant variability in subclone estimates across seeds.

This paper introduces PGDIPS, a physics-guided deep learning method for stain deconvolution in histopathology images, achieving better generalization and interpretability without training data.

This study develops quantitative metrics and simulated datasets to evaluate subclonal reconstruction methods in tumours.