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Titlebook: Chemical Master Equation for Large Biological Networks; State-space Expansio Don Kulasiri,Rahul Kosarwal Book 2021 The Editor(s) (if applic

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樓主: interleukins
11#
發(fā)表于 2025-3-23 12:15:50 | 只看該作者
12#
發(fā)表于 2025-3-23 15:18:47 | 只看該作者
13#
發(fā)表于 2025-3-23 22:04:46 | 只看該作者
An Integrated Large Model Case Study: Solving CME for Oxidative Stress Adaptation in the Fungal PatThe main objective of this chapter is to investigate the performance of the numerical . algorithm on a very large biochemical system. We analyse the state-space, domain formation and probabilities of important species by implementing and integrating the mathematical model of oxidative stress adaptation in the fungal pathogen, ..
14#
發(fā)表于 2025-3-23 22:18:58 | 只看該作者
comprehensively, underlining the interdisciplinary approach .This book highlights the theory and practical applications of the chemical master equation (CME) approach for very large biochemical networks, which provides a powerful general framework for model building in a variety of biological networ
15#
發(fā)表于 2025-3-24 04:28:23 | 只看該作者
16#
發(fā)表于 2025-3-24 06:30:26 | 只看該作者
Visualizing Markov Process Through Graphs and Trees,onditions that must be followed by the functions. We quickly discover that the state-space problem can be simplified by characterization of a Markov chain that requires the graphs that adheres to the Markov chain tree properties. In this chapter, we visualize stochastic processes as Markov chain trees.
17#
發(fā)表于 2025-3-24 14:12:48 | 只看該作者
18#
發(fā)表于 2025-3-24 16:23:23 | 只看該作者
Introduction,e biochemical pathways can be modelled as reaction networks and these networks tend to be very large. We require novel computing and mathematical methods to deal with enormous amounts of experimental data down to the level of a single molecule of a species and then to use the data to develop phenomologial models.?
19#
發(fā)表于 2025-3-24 21:31:34 | 只看該作者
Intelligent State Projection,assive size of the transition rate matrix . and the time complexity of the evaluation of the matrix exponential increases. Therefore, we propose . (.) algorithm, which aims to improve the strategy of the state-space expansion and computing efficiency.
20#
發(fā)表于 2025-3-25 00:18:08 | 只看該作者
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