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Neural network aided approximation and parameter inference of non-Markovian models of gene expression
- Source :
- Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Portfolio, 2021.
-
Abstract
- Cells are complex systems that make decisions biologists struggle to understand. Here, the authors use neural networks to approximate the solution of mathematical models that capture the history and randomness of biochemical processes in order to understand the principles of transcription control.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 12
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.4bc73034fff748fc9da54f683d9b7be8
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-021-22919-1