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This work asks whether a self-architecting transformer, which grows its own width and depth from quantitative signals derived from the attention matrices, can extract competitive protein representations from a single reference proteome.
An integrated whole-genome and transcriptome workflow is developed to systematically distinguish functionally credible, predictive driver aberrations from non-functional alterations across all classes of genomic events in ovarian high-grade serous carcinoma.
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