Self-supervised learning of multi-omics embeddings in the low-label, high-data regime

Christian John Hurry, Emma Slade

Contrastive, self-supervised learning (SSL) is used to train a model that predicts cancer type from miRNA, mRNA or RPPA expression data. This model, a pretrained FT-Transformer, is…