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RESEARCH PROGRAM

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Keywords
SYSTEMS BIOLOGY; BIOCONCURRENCY; BIO-INSPIRED CALCULI AND MODELS

Systems Biology: modeling, languages and analysis (Sybilla)

Università degli Studi di Trento
Abstract
We plan to determine techniques to model (both at a linguuistic and at a graphic level) complex biological systems. We then equip our formalisms with tools to analyse the dynamic behaviour and the dynamic evolution of the system in hand recovering most of the results coming from concurrency and language theory. We also exploit in this project results from the simulation world by including quantitative information in the specifications of the case studies. Eventually, we also investigate how logical formalisms can be used and adapted to the new biological applicative domain.

The above development is tuned, tested and validated over case studies coming from the literature and from the interactions that any group involved in this project has with biologists under other funded initiatives.

The feasibility of the approach is shown by realizating proof-of-concept software tools based on the theoretical framework developed in the first phase of the investigation.

The main focus of the activities reported here is on the computer science side as they should produce new language primitives and analysis tools that are then instantiated to a biological setting. The positive side effect of this research is that new computational paradigms could emerge taking inspiration from the way in which living matter process information.

Principal Investigator
Corrado PRIAMI Università degli Studi di TRENTO
Research Objectives
The ultimate goal of systems biology is to predict the behavior of living matter. If we can devise framework that can model biological systems and analyse and simulate them, then are on the right track. Ultimately, we want to understand the functioning of cells at useful levels of abstraction, and we want to be able to predict unknown behavior. Those achievement should then enable us to use biological matter as flexible information and material processing devices.

First Results
The results attended out of this phase are:

- definition of new primitives for modeling biological systems through process calculi and their stochastic extension to cope with quantitative parameters;

- new models based on hybrid automata and temporal logics taking inspiration from biological phenomena;

- Extension of membrane systems with probabilities to define interaction within biological systems;The expected results are:

- generalization of hybrid automata and definition of efficient algorithms to analyse properties of biological systems;

- definition of basic simulation tools for hybrid models, process calculi and membrane systems;

- new techniques to handle the protein folding problem;

- re-use of existing tools to model check logical specifications of biological systems;

- cross-influence between computer security and biological models of, e.g., the immune system;The expected results are:

- modeling and analysis of biological case studies to tune and validate the ideas and tools proposed;

Timescale
24 months
National and international background
One of the main problems of contemporary biology is understanding the dynamics of genes and proteins inside the cellular molecular machinery, when they give rise to a living organism [Kitano02]. Unfortunately, nowadays there are no experimental techniques able to track the dynamics of the complete metabolome of a cell. A promising approach is to represent all the known relationships between the elements in a metabolome in silico, so building up a sort of a virtual cell [LS01]. There are many proposals of biochemical modelling [GP98,DL03,NOMK99] (see also www.cellml.org). Here, we concentrate our attention to those based on formal methods.

We shall briefly survey those approaches that exploit the similarities between networks of biochemical cells and networks of computing processes. Indeed, a network of bio-cells can be seen as a computing machinery, made of processing agents which interact and cooperate to achieve a common goal. Agents autonomously compute on their own and exchange information with each other [RS02]. This informal description applies to concurrent system as well, in the so-called global computing field. These systems are made of large number of geographically dispersed, possibly mobile and communicating computing agents. It is thus natural to use techniques from the global computing field to study the behaviour of biological cells. Particularly promising is the use of process calculi, which are formalisms used to describe mobile, concurrent >>>