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Titlebook: Computational Methods in Systems Biology; 21st International C Jun Pang,Joachim Niehren Conference proceedings 2023 The Editor(s) (if appli

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11#
發(fā)表于 2025-3-23 10:09:17 | 只看該作者
https://doi.org/10.1007/978-3-642-00854-2 derivative CRN, most of which being models of oscillators and control systems in the cell, and discuss in detail two such examples: one model of the circadian clock and one model of a bistable switch.
12#
發(fā)表于 2025-3-23 16:03:59 | 只看該作者
Information procurement decisionsin this context. Therefore, Harissa can be used both as an inference tool, to reconstruct biologically relevant networks from time-course scRNA-seq data, and as a simulation tool, to generate quantitative gene expression profiles in a non-trivial way through gene interactions.
13#
發(fā)表于 2025-3-23 22:04:20 | 只看該作者
Overview of decision-making procedurefference between the output variables in the original and reduced model, is in the order of .. Furthermore, we provide a heuristic algorithm to find the smallest . for a given maximal approximation error. Finally, we demonstrate the approach in biological models from the literature by providing coar
14#
發(fā)表于 2025-3-23 22:41:03 | 只看該作者
15#
發(fā)表于 2025-3-24 05:53:18 | 只看該作者
16#
發(fā)表于 2025-3-24 09:23:55 | 只看該作者
Conference proceedings 2023ected from 28 submissions. CMSB focuses on modeling, simulation, analysis, design and control of biological systems and covers the broad field of computational methods and tools in systems and synthetic biology and their applications. ?.
17#
發(fā)表于 2025-3-24 11:51:12 | 只看該作者
18#
發(fā)表于 2025-3-24 15:31:22 | 只看該作者
19#
發(fā)表于 2025-3-24 22:29:49 | 只看該作者
Developing and evaluating optionsl framework) or both cells (population framework). For both frameworks, we find an exact time-independent distribution of protein concentration and cell volume. We explore the consequences of dilution feedback on ergodicity, population growth rate, and the bias of the population distribution towards faster growing cells with less protein.
20#
發(fā)表于 2025-3-25 00:32:19 | 只看該作者
,Attractor Identification in?Asynchronous Boolean Dynamics with?Network Reduction,of candidate attractor states, which are then screened with techniques of reachability analysis combined with trap space computation. An implementation that brings together recently developed Boolean network analysis tools, tested on biological models and random benchmark networks, shows the potential to significantly reduce running times.
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