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Computational Methods in Systems Biology
This book constitutes the refereed proceedings of the 15th International Conference on Computational Methods in Systems Biology, CMSB 2017, held in Darmstadt, Germany, in September 2017. The 15 full papers, 4 tool papers and 4 posters presented together with 1 invited talk were carefully reviewed and selected from 41 regular paper submissions. Topics of interest include formalisms for modeling biological processes; models and their biological applications; frameworks for model verication, validation, analysis, and simulation of biological systems; high-performance computational systems biology and parallel implementations; model inference from experimental data; model integration from biological databases; multi-scale modeling and analysis methods; and computational approaches for synthetic biology.
Computational Methods in Systems Biology
This book constitutes the refereed proceedings of the 16th International Conference on Computational Methods in Systems Biology, CMSB 2018, held in BRNO, Czech Republic, in September 2018. The 15 full and 7 short papers presented together with 5 invited talks were carefully reviewed and selected from 46 submissions. Topics of interest include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology; parameter and model inference from experimental data; automated parameter and model synthesis; model integration and biological databases; multi-scale modeling and analysis methods; design, analysis, and verification methods for synthetic biology; methods for biomolecular computing and engineered molecular devices. Chapters 3, 9 and 10 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Computational Methods in Systems Biology
This book constitutes the refereed proceedings of the 18th International Conference on Computational Methods in Systems Biology, CMSB 2020, held in Konstanz, Germany, in September 2020.* The 17 full papers and 5 tool papers were carefully reviewed and selected from 30 submissions. In addition 3 abstracts of invited talks and 2 tutorials have been included in this volume. Topics of interest include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology and parallel implementations; model inference from experimental data; model integration from biological databases; multi-scale modeling and analysis methods; computational approaches for synthetic biology; and case studies in systems and synthetic biology. * The conference was held virtually due to the COVID-19 pandemic.
A mathematical modeling framework to simulate and analyze cell type transitions
The quantitative understanding of changes in cell types, referred to as cell type transitions, is fundamental to advance fields such as stem cell research, immunology, and cancer therapies. This thesis provides a mathematical modeling framework to simulate and analyze cell type transitions. The novel methodological approaches and models presented here address diverse levels which are essential in this context: Gene regulatory network models represent the cell type-determining gene expression dynamics. Here, a novel construction method for gene regulatory network models is introduced, which allows to transfer results from generic low-dimensional to realistic high-dimensional gene regulatory n...
Computational Methods in Systems Biology
This book constitutes the proceedings of the 12th International Conference on Computational Methods in Systems Biology, CMSB 2014, held in Manchester, UK, in November 2014. The 16 regular papers presented together with 6 poster papers were carefully reviewed and selected from 31 regular and 18 poster submissions. The papers are organized in topical sections on formalisms for modeling biological processes, model inference from experimental data, frameworks for model verification, validation, and analysis of biological systems, models and their biological applications, computational approaches for synthetic biology, and flash posters.
Computational Methods in Systems Biology
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.
Stochastic Methods for Parameter Estimation and Design of Experiments in Systems Biology
Markov Chain Monte Carlo (MCMC) methods are sampling based techniques, which use random numbers to approximate deterministic but unknown values. They can be used to obtain expected values, estimate parameters or to simply inspect the properties of a non-standard, high dimensional probability distribution. Bayesian analysis of model parameters provides the mathematical foundation for parameter estimation using such probabilistic sampling. The strengths of these stochastic methods are their robustness and relative simplicity even for nonlinear problems with dozens of parameters as well as a built-in uncertainty analysis. Because Bayesian model analysis necessarily involves the notion of prior ...
Computational Methods in Systems Biology
This book constitutes the refereed proceedings of the 13th International Conference on Computational Methods in Systems Biology, CMSB 2015, held in Nantes, France, in September 2015. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 43 full and 4 short paper submissions. The papers cover a wide range of topics in the analysis of biological systems, networks and data such as model checking, stochastic analysis, hybrid systems, circadian clock, time series data, logic programming, and constraints solving ranging from intercellular to multiscale.
Advances in the Theory of Control, Signals and Systems with Physical Modeling
In the 60's, control, signals and systems had a common linear algebraic background and, according to their evolution, their respective backgrounds have now dramatically differed. Recovering such a common background, especially in the nonlinear context, is currently a fully open question. The role played by physical models, finite or infinite dimensional, in this hypothetical convergence is extensively discussed in this book. The discussion does not only take place on a theoretical basis but also in the light of two wide classes of applications, among the most active in the current industrially oriented researches: - Electrical and Mechatronical systems; - Chemical Processes and systems appea...
