MINI
W/S
ON "COMPUTATIONAL
APPROACHES
TO BIOLOGY"
(SLIDES)
Scuola di Dottorato
Galileo
Dottorato in
Informatica
Dipartimento di Informatica
Pisa, 18  26 October 2007
(free participation)
for scientific issues:
degano@di.unipi.it
for administrative details:
fierro@di.unipi.it
Preliminary schedule
The idea is to have a programme
as
flexible as possible,
so to foster interactions among participants and to allow lastminute
presentations from them.
October 18th, 2007
Aula Seminari Est  Dip. Informatica
1010:30:
Welcome
10:3012:30: Jane
Hillston  U.
Edinburgh
"BioPepa", "Calculation for Systems Biology"
October 19th, 2007
Aula
Seminari Est  Dip. Informatica
1011:
Corrado Priami, U. & CoSBi Trento
"The Beta Workbench"
1113: Stephen
Gilmore  U.
Edinburgh
"Stochastic simulation for Systems Biology"
October 22nd, 2007
Aula Seminari Est  Dip. Informatica
1011:
Gheorghe
Paun  Ist. Math., Romanian Academy
"Membrane computing. A quick introduction"
1516:
Vincenzo
Manca  U. Verona
"Discrete Mathematical Models of Metabolism"
October
23rd, 2007
Aula
Seminari Est  Dip. Informatica
1011:
Gheorghe
Paun  Ist. Math., Romanian Academy
"Spiking neural P Systems"
1516: Alberto
Policriti  U. Udine
"Hybrid Systems and Systems Biology"
October 24th, 2007
Aula Seminari Est  Dip. Informatica
1011:
Giancarlo
Mauri  U. Milano, Bicocca
"Stochastic modelling of biological systems:
membrane systems in Systems Biology
October 25th, 2007
Aula
Seminari Est  Dip. Informatica
1011:
Emanuela
Merelli  U. Camerino
"Agentbased
Modeling and Simulation in Systems Biology Platform"
1516:
Orkun
Soyer  CoSBi Trento
"Using evolutionary approaches to study signalling pathways"
October
26th, 2007
Aula Seminari Est  Dip. Informatica
1011:
Luca
Cardelli  MRC Cambridge
"Artificial Biochemistry"
ABSTRACTS:
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 picalculus. 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 BioPEPA, a new language tailored to modelling
biochemical reactions. BioPEPA 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
betabinders 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 chemicallyreacting 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 celllike or
tissuelike membrane structure one processes multisets of symbol
objects according to reactionlike rules. Most of the classes of P
systems are Turing universal; when an enhanced parallelism is
available, NPcomplete problems can be solved in polynomial time (by
a spacetime tradeoff, with the space created in a biologically
inspired manner). In the last years, many applications were reported,
especially in biology and biomedicine, 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
Psystems, 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 fastrate growing area of Systems Biology, the last decade
has witnessed
the increasing development of several
computational
methodologies,
modelling approaches, analysis methods and
biotechnological procedures for the holistic investigation of
biological
systems, to the porpuse of gaining a systemlevel
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: Agentbased 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
finegrained molecular world to cell compartments, organisms and
ecosystems. We show
how a Multiagent 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 biochemical 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 (nontrivial,
"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.
