Hybrid systems biology : 6th International Workshop, HSB 2019, Prague, Czech Republic, April 6-7, 2019 : revised selected papers / Milan Češka, Nicola Paoletti (eds.).
Material type:
TextSeries: LNCS sublibrary. SL 8, Bioinformatics. | Lecture notes in computer science. Lecture notes in bioinformatics ; ; 11705.Publisher: Cham, Switzerland : Springer, [2019]Description: 1 online resource (xvi, 181 pages) : illustrations (some color)Content type: - text
- computer
- online resource
- 9783030280420
- 303028042X
- 3030280411
- 9783030280413
- 9783030280437
- 3030280438
- 005.101/5113 23
- QA76.9.L63 H73 2019eb
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eBook
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e-Library | eBook LNCS | Available |
Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed August 29, 2019).
A multimodular system to study the impact of a focal lesion in neuronal cell cultures -- Reachability analysis and hybrid systems biology -- In Memoriam Oded Maler -- Reaction networks, oscillatory motifs and parameter estimation in biochemical systems -- Fixed-point computation of equilibria in biochemical regulatory networks -- Rejection-based simulation of stochastic spreading processes on complex networks -- Controlling noisy expression through auto regulation of burst frequency and protein stability -- Extracting landscape features from single particle trajectories -- A hybrid HMM approach for the dynamics of DNA methylation -- Using a hybrid approach to model central carbon metabolism across the cell cycle -- Data-informed parameter synthesis for population Markov chains-. rPrism -- A software for reactive weighted state transition models -- Hybrid modeling of metabolic-regulatory networks.
This book constitutes the thoroughly refereed proceedings of the 6th International Workshop on Hybrid Systems Biology, HSB 2019, held in Prague, Czech Republic, in April 2019. The 8 full papers presented in this book together with 1 short paper and 3 invited papers were carefully reviewed and selected from 13 submissions. They cover topics such as: modeling and analysis of metabolic, signaling, and genetic regulatory networks in living cells; models of tissues, organs, physiological models; models and methods coping with incomplete, uncertain and heterogeneous information including learning for biological systems, parametric synthesis and inference; stochastic and hybrid models in biology; hierarchical systems for multi-scale, multi-domain analysis; abstraction, approximation, discretization, and model reduction techniques; modeling, analysis and design for synthetic biology, cyber-biological systems and biomedical studies (e.g. therapies, teleoperation); game-theoretical frameworks and population models in biology (e.g. mixed-effects and Bayesian modeling); biological applications of quantitative and formal analysis techniques (e.g. reachability computation, model checking, abstract interpretation, bifurcation theory, stability and sensitivity analysis); efficient techniques for combined and heterogeneous (stochastic/deterministic, spatial/non-spatial) simulations for biological models; modeling languages and logics for biological systems with related analysis and simulation tools; and control architectures of biological systems including biology-in-the-loop systems and bio-robotics.
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