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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...
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| Publicat a: | Bioinformatics |
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| Autors principals: | , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Oxford University Press
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8055224/ https://ncbi.nlm.nih.gov/pubmed/32706854 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa673 |
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