The Tissue and Cell mark-up languages are based on open standards like the XML markup language. Known Cell scale ML languages are CellML and SBML. The purpose of using Mark-up languages is to store and exchange computer-based mathematical models. It allows scientists to share models even if they are using different model-building software. It also enables them to reuse components from one model in another, thus accelerating model building. This level of modelling includes information about model structure (how the parts of a model are organizationally related to one another), mathematics (equations describing the underlying processes) and metadata (additional information about the model that allows scientists to search for specific models or model components in a database or other repository). Both CellML and SBML includes mathematics and metadata by leveraging existing languages, including MathML and RDF.

In our laboratory we work on extending these mark-up languages in order to specify data and define computation, simulation and rendering information. All our Computational studies are based on the BioPSis framework.

In cellular electrophysiology, computational, modeling and visualization tools of multidimensional simulations have become indispensable for the development of new models with enormous computational requirements. Computational demands, under specific circumstances may be overwhelmed by distributed computations. The current trend in modeling is to express and exchange biological models using CellML and SBML. Frameworks enabling the visualization of multidimensional simulations and providing an interactive environment are needed. The simulations can be either 0D or multidimensional. However, the works presented in the literature, focus in 0D or 1D experiments. The existing tools are not reusable by external developers who want to implement new features. Usually, they are implemented in a monolithic way without much internal structuring for additional modules. Furthermore, the implementation of distributed computations, monitoring the computational efficiency and interactive visualization of multidimensional simulations requires different development and design approaches.

In our lab we developed a new tool, called BioPSiS (Biological Process Simulation System), which can be used in the computational simulation of cellular electrophysiology. The overall system architecture and its three main subsystems are shown in Fig. 1. The three subsystems are:

Figure 1: The BioPSiS Overall Architecture design

Our tool has several advantages compared to previous reported tools. It achieves maximum performance in the simulations without sacrificing other functionality specifications. It can be carried out into a personal computer or a cluster of CPUs. The computations can be monitored during execution by the user. The system performance is enhanced by its capability for use of mark-up modeling. The latter is achieved by the use of special modules which represent various computation models. In this work we present the functionalities of the interactive visualization subsystem.

Figure 2: BioPSiS Graphical User Interface

Our interactive visualization tool which has been presented in this article, is a subsystem of BioPSiS. We have presented a set of tools and features capable to provide a promising working framework for biologists. Our framework covers two different needs, the real time monitoring of the simulation processing and the need of an intuitive tool to evaluate the results. The interactive approach we have chosen to develop, allows the user not only to examine the cells on the surface of the tissue but also the cells located under the surface of the tissue. The system must be completed with the distributed computation subsystem and with its adaption to an interactive tool. For the moment single unit processes are used for testing and validation of the proposed framework. The handling of the produced simulation data is complicated. One factor is the complexity and the size of the captured information. One other reason is that biologists which are trained to work with biological models are typically not trained to conduct distributed computational operations. Shell interfaces and computations based on interpreter can be beneficial only under strict circumstances. However, our aim is to give the opportunity in scientific centers to obtain powerful computational platforms with practical intuitive tools. These computational platforms will be based on clusters of inexpensive PCs.