Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. Results: Here, we present COPASI, a platform-independent and userfriendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. Availability: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel) and Sun Solaris (SPARC), as well as the full source code under an open source license from http://www.

The specification of SBML Level 1 is freely available from http://www.sbml.org/

Content Summary414I.Introduction415II.Ca2+ importer and exporter in plants415III.The Ca2+ decoding toolkit in plants415IV.Mechanisms of Ca2+ signal decoding417V.Immediate Ca2+ signaling in the regulation of ion transport418VI.Ca2+ signal integration into long‐term ABA responses419VIIIntegration of Ca2+ and hormone signaling through dynamic complex modulation of the CCaMK/CYCLOPS complex420VIIICa2+ signaling in mitochondria and chloroplasts422IXA view beyond recent advances in Ca2+ imaging423XModeling approaches in Ca2+ signaling424XIConclusions: Ca2+ signaling a still young blooming field of plant research424Acknowledgements425ORCID425References425 Summary Temporally and spatially defined changes in Ca2+ concentration in distinct compartments of cells represent a universal information code in plants. Recently, it has become evident that Ca2+ signals not only govern intracellular regulation but also appear to contribute to long distance or even organismic signal propagation and physiological response regulation. Ca2+ signals are shaped by an intimate interplay of channels and transporters, and during past years important contributing individual components have been identified and characterized. Ca2+ signals are translated by an elaborate toolkit of Ca2+‐binding proteins, many of which function as Ca2+ sensors, into defined downstream responses. Intriguing progress has been achieved in identifying specific modules that interconnect Ca2+ decoding proteins and protein kinases with downstream target effectors, and in characterizing molecular details of these processes. In this review, we reflect on recent major advances in our understanding of Ca2+ signaling and cover emerging concepts and existing open questions that should be informative also for scientists that are currently entering this field of ever‐increasing breath and impact.

We present a new model for calcium oscillations based on experiments in hepatocytes. The model considers feedback inhibition on the initial agonist receptor complex by calcium and activated phospholipase C, as well as receptor type-dependent self-enhanced behavior of the activated G(alpha) subunit. It is able to show simple periodic oscillations and periodic bursting, and it is the first model to display chaotic bursting in response to agonist stimulations. Moreover, our model offers a possible explanation for the differences in dynamic behavior observed in response to different agonists in hepatocytes.

Computational modeling and simulation of biochemical networks is at the core of systems biology and this includes many types of analyses that can aid understanding of how these systems work. COPASI is a generic software package for modeling and simulation of biochemical networks which provides many of these analyses in convenient ways that do not require the user to program or to have deep knowledge of the numerical algorithms. Here we provide a description of how these modeling techniques can be applied to biochemical models using COPASI. The focus is both on practical aspects of software usage as well as on the utility of these analyses in aiding biological understanding. Practical examples are described for steady-state and time-course simulations, stoichiometric analyses, parameter scanning, sensitivity analysis (including metabolic control analysis), global optimization, parameter estimation, and stochastic simulation. The examples used are all published models that are available in the BioModels database in SBML format.