David Morgan Thomas

The paper develops a thermodynamic model linking transcriptome organization to growth state by analyzing RNA folding free energies across cell cycle and stress adaptation.

This paper develops patient-derived tumour models using engineered ECM hydrogels to enable precision medicine for paediatric cancers by retaining tumour genotype and phenotype.

ProCanFDL uses federated deep learning to subtype cancers using proteomic data while preserving privacy, achieving performance gains over local models.

mity detects low heteroplasmy mitochondrial variants in whole genome sequencing data, improving diagnostic rates for mitochondrial diseases.

The paper presents a streamlined system for integrating 3D protein structures into variant analysis, enabling easy variant specification and access to structural insights.

ClinSV detects structural and copy number variants from whole genome sequencing data with high sensitivity and low false positive rates, outperforming clinical microarrays in identifying reportable variants.

The paper estimates cancer-specific penetrance in Li-Fraumeni syndrome using a statistical model and validates it across multiple cohorts, showing age-dependent risk patterns for different cancer types.

The paper introduces the Medical Genome Reference Bank, a resource of whole genome sequences and phenotypes from 2,570 healthy elderly Australians, showing fewer disease-associated variants and age-related somatic changes linked to grip strength.

The paper introduces the Medical Genome Reference Bank (MGRB), a whole-genome dataset of 4,000 healthy elderly individuals, to serve as a reference for genetic variant analysis and healthy aging research.

EPICC clusters cancer patients using DNA mutation profiles and protein interactions, identifying new cross-tissue cancer groups and protein modules.

The paper uses whole genome optical mapping to reveal complex chained fusion events and novel sequences in cancer genomes that are not detected by short-read sequencing.