How Can Gene-Expression Information Improve Prognostic Prediction in TCGA Cancers: An Empirical Comparison Study on Regularization and Mixed Cox Models

BACKGROUND: Previous cancer prognostic prediction models often consider only the most important transcriptomic expressions, and their power is limited. It is unknown whether prediction power can be further improved when additional transcriptomic information is incorporated. METHODS: To integrate tra...

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Detalles Bibliográficos
Autores principales: Yu, Xinghao, Wang, Ting, Huang, Shuiping, Zeng, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472843/
https://www.ncbi.nlm.nih.gov/pubmed/32973875
http://dx.doi.org/10.3389/fgene.2020.00920

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472843/
https://www.ncbi.nlm.nih.gov/pubmed/32973875
http://dx.doi.org/10.3389/fgene.2020.00920

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