Feature screening for survival trait with application to TCGA high-dimensional genomic data

BACKGROUND: In high-dimensional survival genomic data, identifying cancer-related genes is a challenging and important subject in the field of bioinformatics. In recent years, many feature screening approaches for survival outcomes with high-dimensional survival genomic data have been developed; how...

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Detalles Bibliográficos
Autores principales: Wang, Jie-Huei, Li, Cai-Rong, Hou, Po-Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Bioinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918142/
https://www.ncbi.nlm.nih.gov/pubmed/35291482
http://dx.doi.org/10.7717/peerj.13098

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918142/
https://www.ncbi.nlm.nih.gov/pubmed/35291482
http://dx.doi.org/10.7717/peerj.13098

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