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Integrative Gene Network Construction to Analyze Cancer Recurrence Using Semi-Supervised Learning
BACKGROUND: The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses...
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| Главные авторы: | , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Public Library of Science
2014
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3908883/ https://ncbi.nlm.nih.gov/pubmed/24497942 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0086309 |
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