Titlebook: Computational Methods in Systems Biology; 18th International C Alessandro Abate,Tatjana Petrov,Verena Wolf Conference proceedings 2020 Spri

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Choosing, and Being, a Good Mentornguages and concurrency, and 2) mean field approximations (MFAs), a collection of approximation techniques ubiquitous in the study of complex dynamics. Using existing tools from algebraic graph rewriting, as well as new ones, we build a framework which generates rate equations for stochastic GTSs an

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C. Max Schmidt M.D., Ph.D., MBA molecule fluctuates in time due to the random occurrence of production and degradation reactions. Here we consider a stochastic model for a self-regulating transcription factor whose lifespan (or time till degradation) follows a general distribution modelled as per a multi-dimensional phase-type pr

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https://doi.org/10.1007/978-0-85729-313-8ation principles are abstracted away to focus on the main dynamical properties of the network structure. In their interpretation by ordinary differential equations, we say that a CRN with distinguished input and output species computes a positive real function ., if for any initial concentration . o

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Writing a Grant/Obtaining Funding When the variable is exactly constant, one talks about absolute concentration robustness (ACR). A dual and equally important property is ., which means that the system has multiple steady states and possible outputs, at constant parameters. We propose a new computational method based on interval te

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https://doi.org/10.1007/978-3-030-14644-3states and transitions. For biological systems, it becomes a challenging task to compare such mathematical objects with biological knowledge, or interpret the transitions inside an attractor in terms of the sequence of events in a biological cycle. A recent methodology generates summary graphs to he