David M. Malkin

This study shows that mutant p53 alters gut microbiota interactions, leading to bile acid changes that promote distal tumour growth.

This study characterizes zebrafish models of Li-Fraumeni syndrome with TP53 mutations, showing dysfunctional p53 pathways, tumor development, and mutation-specific phenotypes.

This study uses cancer mutation data and machine learning to predict the pathogenicity of germline missense variants, showing strong performance in identifying disease-causing variants.

This study evaluates an integrated liquid biopsy approach for early cancer detection in Li-Fraumeni syndrome patients, showing improved detection rates compared to individual methods.

The paper identifies four immune clusters in pediatric nervous system tumors using RNA-seq data and validates them with multiple methods, highlighting the need for personalized immunogenomic profiling.

CanDIG enables secure, federated genomic and health data analysis across jurisdictions while maintaining data locality and privacy.

The paper optimizes CRISPR/Cas9-mediated point mutation knock-in in zebrafish using allele-specific PCR assays and identifies key factors improving knock-in efficiency and reducing false positives.