Inferring a nonlinear biochemical network model from a heterogeneous single-cell time course data
Abstract Mathematical modeling and analysis of biochemical reaction networks are key routines in computational systems biology and biophysics; however, it remains difficult to choose the most valid model. Here, we propose a computational framework for data-driven and systematic inference of a nonlin...
Guardado en:
Autores principales: | Yuki Shindo, Yohei Kondo, Yasushi Sako |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
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Materias: | |
Acceso en línea: | https://doaj.org/article/82ad5b244fc04aa09dfb7172228676c1 |
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