Prima Sanjaya

muat: portable transformer-based method for tumour classification and representation learning from somatic variants

The paper introduces muat, a transformer-based tool for tumour classification using somatic variants, achieving high accuracy across different cohorts without retraining.

Pan-cancer tumour classification and risk stratification from whole-genome somatic variants via dual-task representation learning

MuAt2, a Transformer model, classifies tumour types and subtypes from somatic variants, improving accuracy and calibration across cancer types and cohorts.

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping

The paper introduces MuAt, a deep learning model that learns representations of somatic mutations to predict tumour types and subtypes with high accuracy.