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A High-Performance Computing Implementation of Iterative Random Forest for the Creation of Predictive Expression Networks
As time progresses and technology improves, biological data sets are continuously increasing in size. New methods and new implementations of existing methods are needed to keep pace with this increase. In this paper, we present a high-performance computing (HPC)-capable implementation of Iterative R...
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| Publicat a: | Genes (Basel) |
|---|---|
| Autors principals: | , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2019
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6947651/ https://ncbi.nlm.nih.gov/pubmed/31810264 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/genes10120996 |
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