Sparse Regression in Cancer Genomics: Comparing Variable Selection and Predictions in Real World Data

BACKGROUND: Evaluation of gene interaction models in cancer genomics is challenging, as the true distribution is uncertain. Previous analyses have benchmarked models using synthetic data or databases of experimentally verified interactions – approaches which are susceptible to misrepresentation and...

Descripción completa

Detalles Bibliográficos
Autores principales: O’Shea, Robert J, Tsoka, Sophia, Cook, Gary JR, Goh, Vicky
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640984/
https://www.ncbi.nlm.nih.gov/pubmed/34866896
http://dx.doi.org/10.1177/11769351211056298

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640984/
https://www.ncbi.nlm.nih.gov/pubmed/34866896
http://dx.doi.org/10.1177/11769351211056298

Ejemplares similares