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...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
SAGE Publishing
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/d2c6613ebad14b04be7cce97ef0de93f |
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