Inference of Cancer Progression With Probabilistic Graphical Model From Cross-Sectional Mutation Data
With the advance of high-throughput sequencing technologies, a great amount of somatic mutation data in cancer have been produced, allowing deep analyzing tumor pathogenesis. However, the majority of these data are cross-sectional rather than temporal, and it is difficulty to infer the temporal orde...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8338000/ |