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Rank‐based Bayesian variable selection for genome‐wide transcriptomic analyses
Variable selection is crucial in high‐dimensional omics‐based analyses, since it is biologically reasonable to assume only a subset of non‐noisy features contributes to the data structures. However, the task is particularly hard in an unsupervised setting, and a priori ad hoc variable selection is s...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley & Sons, Inc.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9796757/ https://www.ncbi.nlm.nih.gov/pubmed/35844145 http://dx.doi.org/10.1002/sim.9524 |