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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Detalles Bibliográficos
Autores principales: Park, Chihyun, Ahn, Jaegyoon, Kim, Hyunjin, Park, Sanghyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3908883/
https://www.ncbi.nlm.nih.gov/pubmed/24497942
http://dx.doi.org/10.1371/journal.pone.0086309

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3908883/
https://www.ncbi.nlm.nih.gov/pubmed/24497942
http://dx.doi.org/10.1371/journal.pone.0086309

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