**General Actions:**

- Membrane Computing
- Extension of Bio-PEPA
- Versari extension of stochastic pi-calculus (Spi@)
- Jasmin Fisher
- BioSPICE (Claire Tomlin): modeling and simulation of spatio-temporal processes in living cells
- Cellerator and xCellerator-- based on Mathematica, ma sembra avere TUTTO, vedi paper
- CompuCell

- The technical report Process Calculi Abstractions for Biology is a very useful reading when you start with Process Algebra applied in Systems Biology. It gives a brief overview of the general principles founding the Systems Biology discipline, and afterwards it makes a review on the process calculi that have been already used for modelling biological systems.
- The technical report Stochastic pi-calculus modelling of multisite phosphorylation based signaling: in silico analysis of the Pho4 transcription factor and the PHO pathway in Saccharomyces cerevisiaees cerevisiae is a very important and useful work, as "the biological contributions of this work represent the first biological predictions obtained with process calculi based approaches".
It provides:
- An introduction at the basic concepts of stochastic pi-calculus. These informations are clear and useful.
- A case study as example: the PHO pathway in Saccharomyces cerevisiae. This pathway is responsible of the regulation of inorganic phosphate (
*P_{i}*) concentration inside the cell. The biological behaviour of this system is quite detailed. - A whole section for the introduction of the pi-calculus model of the PHO pathway. The entire model is subdivided in sub-models, each one representing a process inside the pathway. These sub-models are specified as general as possible because they have a general biological valence and can be useful for other pathways. As a result in this section we can find a great example of already built models for phosphorilation, transcription and its regulation through transcription factors, transmembrane transport, protein synthesis and degradation.

- The paper Invited Talk: A Process Algebra Master Equation establishes a basic connection between two formalisms for modelling stochastic phenomena:
*chemical master equations*and*process algebra*.

The paper identifies a Master Equation,*i.e.*, the time differential of the conditional probability of entering a state minus the probability of exiting the state, of a stochastic process algebra. After it compares such equation with the more classical chemical master equations defined by a set of chemical reactions.

Through an often hard mathematic, it proves that a Chemical Master Equation is the same as the Process Master Equation. - The paper A Process Model of Rho GTP-binding Proteins in the Context of Phagocytosis is an important and useful work, which shows the application of stochastic pi-calculus to an open and complex biological problem (
*i.e.*, the role of Rho GTP-binding protein during phagocytosis process). It also provides a comparison between the model of the same biological system obtained with ODE, both at the modelling and results level. - An other useful example of a biological system's model can be found here A Process Model of Actin Polymerisation .

During the *8th International School on Formal Methods for the Design of Computer, Communication and Software Systems: Computational Systems Biology*, I found particularly interesting some talks about which I am going to refer in the following:

**Daniel Gillespie**gave an interesting talk making a connection between different modelling approaches, beginning from stochastic and moving to deterministic models. He reviewed the theory of stochastic chemical kinetics and derived from it the*chemical master equation*approach and the*stochastic simulation algorithm*. He then showed how, through a series of well defined approximations, it is possible to obtain a series of other approaches, such as*tau-leaping, the chemical langevin and Fokker-Planck equations*, and finally the traditional*ordinary differential equations*. This kind of work is really useful for clarifying the differences between modelling approaches, once we have to choose between them. For the talk's tutorial see Simulation Methods in Systems Biology.**Adelinde Uhrmacher**spoke about the importance of the adoption of multi-level models. She proposed some tools and modeling formalisms which can support the modellers in the formalisation and implementation of multi-levels models (DEVS, BlenX, BioAmbients). For the talk's tutorial see Hierarchical Modeling for Computational Biology.**Corrado Priami**introduced the new language and framework BlenX designed by his research group in CoSBi (Trento, IT), as an extension of the stochastic pi-calculus and of BetaBinders. For the talk's tutorial see The BlenXLanguage: A Tutorial.

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