Biological correlates associated with high-risk breast cancer patients identified using a computational method
Abstract Using a novel unsupervised method to integrate multi-omic data, we previously identified a breast cancer group with a poor prognosis. In the current study, we characterize the biological features of this subgroup, defined as the high-risk group, using various data sources. Assessment of thr...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | npj Breast Cancer |
| Online Access: | https://doi.org/10.1038/s41523-025-00725-y |
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