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Computational Methods Systems Biology: 23rd International Conference, CMSB 2025, Lyon, France, September 10-12, Proceedings
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Computational Methods Systems Biology: 23rd International Conference, CMSB 2025, Lyon, France, September 10-12, Proceedings in Chattanooga, TN
Current price: $64.99
Barnes and Noble
Computational Methods Systems Biology: 23rd International Conference, CMSB 2025, Lyon, France, September 10-12, Proceedings in Chattanooga, TN
Current price: $64.99
Loading Inventory...
Size: Paperback
This book constitutes the refereed proceedings of the 23rd International Conference on Computational Methods in Systems Biology, CMSB 2025, which took place in Lyon, France, during September 10–12, 2025.
The 21 full papers presented in this volume were carefully reviewed and selected from 34 submissions sent to reviews.
They are grouped into the following topics: Boolean Networks; Continuous and Hybrid models; Rule-based models; Model inference and machine learning; Population models and control.
The 21 full papers presented in this volume were carefully reviewed and selected from 34 submissions sent to reviews.
They are grouped into the following topics: Boolean Networks; Continuous and Hybrid models; Rule-based models; Model inference and machine learning; Population models and control.
This book constitutes the refereed proceedings of the 23rd International Conference on Computational Methods in Systems Biology, CMSB 2025, which took place in Lyon, France, during September 10–12, 2025.
The 21 full papers presented in this volume were carefully reviewed and selected from 34 submissions sent to reviews.
They are grouped into the following topics: Boolean Networks; Continuous and Hybrid models; Rule-based models; Model inference and machine learning; Population models and control.
The 21 full papers presented in this volume were carefully reviewed and selected from 34 submissions sent to reviews.
They are grouped into the following topics: Boolean Networks; Continuous and Hybrid models; Rule-based models; Model inference and machine learning; Population models and control.
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