Article

Self-Normalizing Deep Learning for Enhanced Multi-Omics Data Analysis in Oncology

2025-04-07

Abstract excerpt

Investigating multi-omics data is crucial for unraveling the complex biological mechanisms underlying cancer, thereby enabling effective strategies for prevention, early detection, diagnosis, and treatment. However, predicting patient outcomes through the integration of all available multi-omics data remains an understudied topic. We present SeNMo, a self-normalizing deep neural network trained on multi-omics data...

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Literature Corpus work: 7565f40b-1761-50e9-81d4-f949aa8bad7c
DOI: 10.20944/preprints202504.0534.v1

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