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Scalable machine learning-assisted model exploration and inference using Sciope
SUMMARY: Discrete stochastic models of gene regulatory networks are fundamental tools for in silico study of stochastic gene regulatory networks. Likelihood-free inference and model exploration are critical applications to study a system using such models. However, the massive computational cost of...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055224/ https://www.ncbi.nlm.nih.gov/pubmed/32706854 http://dx.doi.org/10.1093/bioinformatics/btaa673 |