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Titlebook: Computational Methods in Systems Biology; 19th International C Eugenio Cinquemani,Lo?c Paulevé Conference proceedings 2021 Springer Nature

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書目名稱Computational Methods in Systems Biology
副標(biāo)題19th International C
編輯Eugenio Cinquemani,Lo?c Paulevé
視頻videohttp://file.papertrans.cn/233/232789/232789.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Methods in Systems Biology; 19th International C Eugenio Cinquemani,Lo?c Paulevé Conference proceedings 2021 Springer Nature
描述This book constitutes the refereed proceedings of the 19th International Conference on Computational Methods in Systems Biology, CMSB 2021, held in Bordeaux, France, September 22–24, 2021.*The 13 full papers and 5 tool papers were carefully reviewed and selected from 32 submissions. The topics of interest include?biological process modelling; biological system model verification, validation, analysis, and simulation; high-performance computational systems biology; model inference from experimental data; multi-scale modeling and analysis methods; computational approaches for synthetic biology; machine learning and data-driven approaches; microbial ecology modelling and analysis; methods and protocols for populations and their variability; models, applications, and case studies in systems and synthetic biology. The chapters "Microbial Community Decision Making Models in Batch", "Population design for synthetic gene circuits", "BioFVM-X: An MPI+OpenMP 3-D Simulator for Biological Systems" are?published open access under a CC BY license (Creative Commons Attribution 4.0 International License).?.* The conference was held in a hybrid mode due to the COVID-19 pandemic..
出版日期Conference proceedings 2021
關(guān)鍵詞adaptive control systems; artificial intelligence; automation; computer networks; computer programming; c
版次1
doihttps://doi.org/10.1007/978-3-030-85633-5
isbn_softcover978-3-030-85632-8
isbn_ebook978-3-030-85633-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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,Greening R. Thomas’ Framework with Environment Variables: A Divide and Conquer Approach,servations are often made under experimental conditions which are not necessarily comparable since they depend on the culture medium for example. The construction of a right modelisation therefore depends on our ability to take into account all this information in a single framework.
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Microbial Community Decision Making Models in Batch and Chemostat Cultures,n microbiome. Such simulations rely on assumptions about the culturing environment, affecting if the culture may reach a metabolically stationary state with constant microbial concentrations. They also require assumptions on decision making by the microbes: metabolic strategies can be in the interes
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Learning Boolean Controls in Regulated Metabolic Networks: A Case-Study,verse-engineer Boolean regulations for transcriptional and signaling networks, but they fail to infer regulations that control metabolic networks. This paper provides a formalisation of the inference of regulations for metabolic networks as a satisfiability problem with two levels of quantifiers, an
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