Scuola di Dottorato Galileo

Dottorato in Informatica
Dipartimento di Informatica
Pisa, 18 - 26 October 2007
(free participation)

for scientific issues:

for administrative details:

Preliminary schedule

The idea is to have a programme as flexible as possible,
so to foster interactions among participants and to allow last-minute
presentations from them.

October 18th, 2007

Aula Seminari Est - Dip. Informatica

10-10:30:  Welcome

10:30-12:30: Jane Hillston - U. Edinburgh
"Bio-Pepa", "Calculation for Systems Biology"

October 19th, 2007

Aula Seminari Est - Dip. Informatica

10-11: Corrado Priami, U. & CoSBi Trento
"The Beta Workbench"

11-13: Stephen Gilmore - U. Edinburgh
"Stochastic simulation for Systems Biology"

October 22nd, 2007

Aula Seminari Est - Dip. Informatica

10-11: Gheorghe Paun - Ist. Math., Romanian Academy
"Membrane computing. A quick introduction"

15-16: Vincenzo Manca - U. Verona
"Discrete Mathematical Models of Metabolism"

October 23rd, 2007

Aula Seminari Est - Dip. Informatica

10-11: Gheorghe Paun - Ist. Math., Romanian Academy
"Spiking neural P Systems"

15-16: Alberto Policriti - U. Udine
"Hybrid Systems and Systems Biology"

October 24th, 2007

Aula Seminari Est - Dip. Informatica

10-11: Giancarlo Mauri - U. Milano, Bicocca
"Stochastic modelling of biological systems:
membrane systems in Systems Biology

October 25th, 2007

Aula Seminari Est - Dip. Informatica

10-11: Emanuela Merelli - U. Camerino
"Agent-based Modeling and Simulation in Systems Biology Platform"

15-16: Orkun Soyer - CoSBi Trento
"Using evolutionary approaches to study signalling pathways"

October 26th, 2007

Aula Seminari Est - Dip. Informatica

10-11: Luca Cardelli - MRC Cambridge
"Artificial Biochemistry"


Jane Hillston

Title: Calculation for Systems Biology

PEPA is a stochastic process algebra which was introduced in the
early 1990s for modelling computer and communication systems.  More recently, there has been some interest in applying PEPA, and other stochastic process algebras, to modelling intracellular networks.
In this talk I will present some background on PEPA and the
modelling style which is adopted for systems biology modelling in
PEPA.  The style is more abstract that the mapping which is commonly
used in other stochastic process algebra models such as the
stochastic pi-calculus.  This will highlight the features which we
consider to be important to capture and the analyses we wish to
access for such systems.  These desirable features are the prime
motivators for Bio-PEPA, a new language tailored to modelling
biochemical reactions.  Bio-PEPA will be presented in some detail
and illustrated on several biological examples.


Corrado Priami

Title: The Beta Workbench

Abstract: Systems biology aims at understanding
the dynamic behaviour of biological systems
through the reconstruction of chemical reactions
and simulation of interaction dynamics.
Many approaches include modelling techniques to
represent and analyse dynamics of complex
pathways. In particular, process calculi have
been recently applied to model and simulate
biological systems.
We designed a new language derived from the
beta-binders process calculus to describe dynamic
biological systems, and a set of tools to
generate, compile, simulate and analyse models
written in this language.
The talk will describe the new language and the related tools.


Stephen Gilmore

Title: Stochastic Simulation for Systems Biology

Abstract: This talk is an overview of the use of stochastic
simulation to evaluate models of chemically-reacting systems,
particularly those methods based on the use of Gillespie's Stochastic
Simulation Algorithm (SSA).  The talk will compare with the classical
method of evaluation based on ordinary differential equations and
consider the strengths and weaknesses of both approaches.  Recent
attempts to accelerate stochastic simulation will also be reviewed.



Gheorghe Paun

Title: Membrane computing.
A quick introduction

Abstract: Membrane computing is a branch of natural computing
initiated in 1998 and aiming to learn computing ideas/models from the
structrure and functioning of the living cell. Several types of
computing models - called P systems - were introduced in this
framework. Very shortly, in the compartments of a cell-like or
tissue-like membrane structure one processes multisets of symbol
objects according to reaction-like rules. Most of the classes of P
systems are Turing universal; when an enhanced parallelism is
available, NP-complete problems can be solved in polynomial time (by
a space-time trade-off, with the space created in a biologically
inspired manner). In the last years, many applications were reported,
especially in biology and bio-medicine, but also in computer science,
linguistics, economics, etc.
The talk will give the basic elements of membrane computing and will
present samples of results of the above mentioned types.


Vincenzo Manca

Title: Discrete Mathematical Models of Metabolism

Abstract: Metabolism is the basis of the biomolecular processes of
life. In its abstract and simplest setting a metabolic system is
constituted by a "reactor" (a cell) containing a population of
(bio)molecules of some given types, and  communicating with an
environment from/to which it gets/expels matter and/or energy.  In
this reactor some reactions are active which transform molecules into
other kinds of molecules, according to some stoichiometric patterns.
These reactions have to satisfy some chemical principles which can be
formulated in very general symbolic terms. Metabolic P systems,
shortly MP systems,  are a special class of P systems, introduced for
expressing biological metabolism in discrete terms. Their dynamics is
computed by "metabolic algorithms" which transform populations of objects  according to a "mass partition" principle.  The basic principles of  MP systems are given and a some regulation mechanisms are explained,  which allow us to construct computational models from experimental data of real metabolic processes.


Gheorghe Paun

Title: Spiking neural P systems

Abstract: With inspiration from the way the neurons communicate by
means of electrical impulses of identical shapes (spikes), spikin
neural P systems were introduced. There are several classes of such
systems, most of them equivalent in power with Turing machines. The
complexity investigations in this area is at the beginning, but
already interesting results were obtained.
The talk will present the basic ideas of spiking neural P systems,
some typical results about their computing power, small universal
spiking neural P systems recent results concerning the possibility of
using these systems for solving complex problems. Several research
topics will be mentioned.

 Alberto Policriti

Title: "Hybrid Systems and Systems Biology"

We introduce hybrid systems and discuss some interesting
applications for them proposed to Systems Biology so far.
Then we will talk about the role hybrid systems can have within the
framework of the correspondence between stochastic process algebras  (SPA) and models based on differential equations.
We start defining a syntactic procedure translating programs written in stochastic Concurrent Constraint Programming (sCCP, a SPA)
into a set of Ordinary Differential Equations (ODE) - as well as the inverse procedure translating ODE's into sCCP programs. We observe then how preserving behavior for such a translation in interesting cases, leads naturally to the introduction of hybrid
systems in the picture

Giancarlo Mauri

Title: Stochastic modelling of biological systems: membrane systems
in Systems Biology

Abstract: The talk will present an extension of membrane systems,
 or P-systems, introduced by G. Paun as a bioinspired model of computation,  with stochastic features, and their application to modelling some biological  systems, in the frame of systems biology.
Within the fast-rate growing area of Systems Biology, the last decade
witnessed the increasing development of several computational
methodologies, modelling approaches, analysis methods and
procedures for the holistic investigation of biological
to the porpuse  of gaining a system-level understanding of their complex  structure and dynamics.
In this area, mathematical modelling can be broadly classified into
 deterministic and continuous approaches, based on laws of mass action, and stochastic approaches, which take into consideration the discrete character of the quantity of components and the intrinsie randomness of biological phenomena. Biological systems, in particular cellular processes, can involve a huge number of biochemical precesses, but the amount  of many molecular species can be in the order of tens or hundreds. In these conditions, the deterministic approaches are pushed to their limits and cannot be always reliable,
while the stochastic methods can account for the randomness that can
emerge and dominate the global behaviour of the system.

For this reason, we developed a modelling approach of discrete,
stochastic and compartmentalized type, based on membrane systems,
to describe the system components, their mutual interactions and the noisy behaviour intrinsic in the dynamics.


Emanuela Merelli

Title: Agent-based Modeling and Simulation in Systems Biology platform

Abstract: The agent approach allows natural modeling and programming of biological systems at different levels of abstractions: from the fine-grained molecular world to cell compartments, organisms and ecosystems. We show how a Multi-agent System and suitable Coordination Models can be used to simulate biological processes. We present an application of Multi Agent Systems to model and simulate the pathway of glycoysis.
We model bio-chemical reactions at molecular level. The molecules
move and react in a virtual space using space and time Coordination.
We discuss the implementation of the simulation over a GRID.



Orkun Soyer

Title: Using evolutionary approaches to study signaling pathways

Abstract: Biological pathways are the result of evolution, rather
than design. Thus, understanding how evolutionary dynamics affect
pathways is important for accomplishing a complete understanding how these systems work. I will present a novel approach, that aims to
distill key information on pathway structure and dynamics by studying
their evolution in silico. Using simple mathematical models of
pathways and evolutionary simulations, this approach aims to
understand key system properties and the effects of evolutionary
dynamics on their emergence and diversity.


Luca Cardelli

Title: Artificial Biochemistry

Systems Biology is a new discipline aiming to understand the behavior
of biological systems as it results from the (non-trivial,
"emergent") interaction of biological components. In addition to
analyzing existing biological networks to understand their function,
it is also important to understand from the ground up what simple
networks of interacting components "can do". That investigation can
be carried out in abstract "artificial" frameworks, as long as the
ground rules are kept close enough to the ones of biochemistry. We
discuss some biologically inspired networks that are characterized by
simple components, but by complex interactions. Subtle and unexpected behavior emerges even from simple circuits, and yet stable behavior emerges too, giving some hints about what may be critical and what may be irrelevant in the organization of biological networks.