DoGMA: A Central-Dogma-Guided Foundation Model for Multi-Omics Alignment and Multi-Task Learning in Oncology
DoGMA demonstrates that domain-specific inductive biases can improve the robustness and transferability of multi-omics foundation models, offering new insights into the design of attention mechanisms for multi-omics representation learning.
Junfei Ling, Bangzheng Pu, Bing-Sen Xue et al.
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