Noshad Hosseini

This study identifies genomic drivers of progression and therapeutic outcomes in mCRPC and develops a multi-omic classifier to predict patient survival across multiple therapies.

HLAProphet improves HLA protein quantification by using personalized allele information from DNA sequencing, increasing peptide identifications and aligning with RNA expression and loss of heterozygosity.

MHCnvex is a likelihood-based model for accurately calling copy number variations and loss of heterozygosity in MHC class I and II loci, improving accuracy by integrating adjacent chromosome 6 regions.

The paper develops a two-stage neural network model for liver cancer prognosis using histopathology and transcriptomic data, showing improved accuracy compared to existing methods.