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| ESPERIMENTO TO61, RESPONSABILE: Michele Caselle |
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Negli ultimi anni si e' assistito ad un sempre maggiore utilizzo
dei metodi e degli approcci tipici della fisica teorica
in altri ambiti scientifici ed in particolare in biologia.
L'attitudine alla modellizzazione (tipica della meccanica statistica e
della teorie dei campi quantistica) accompagnata dall'uso di metodi di
simulazione numerica sofisticati si e' mostrata di grandissima utilita' per
studiare sistemi caratterizzati da un gran numero di gradi di
liberta'. La nostra iniziativa si inserisce in questo ambito. La nostra
attivita' di ricerca si concentra principalmente in tre direzioni:
1] Uso di metodi numerici (dinamica molecolare e metodi montecarlo) per lo
studio di interazioni tra proteine e per la dinamica del folding
2] Uso di metodi di teoria dei grafi per lo studio di network biologici
3] Uso di metodi tipici della meccanica statistica dei sistemi complessi per lo
studio di vari problemi di interesse per la biologia e la genomica quali ad
esempio:
- la regolazione dell'espressione genica
- la risposta del sistema immunitario in presenza di stimoli esterni
- la flessibilita' di strutture macromolecolari (DNA o proteine)
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| OBIETTIVI DELL'ESPERIMENTO TO61 |
Title:
Biological applications of theoretical physics methods.
- Introduction
The common feature of the various research projects of the TO61 group is
the use of theoretical physics methods to model and analyse complex systems of biological and
physiological origin.
Generally speaking there are two natural ways
in which theoretical physics methods may play
an important role in addressing problems related to biology:
- by extending and applying to biological systems the existing
experience in modeling and analysis of many-body physical systems in
an effort to bridge the constituent description with the systemic
level of functionality.
- by exporting the skills gained in statistical and particle theories
to the field of biocomputation in order to extract informations
from the huge amount of experimental data that are presently available in
modern "post-genomic" biology.
The domain of biological systems indeed provides several excellent examples
(from protein folding to the clusterization of microarray data)
of problems in which significant results can be obtained by integrating the
work of the experts in the specific field (biologists, biochemists,
biophysicists) with the expertise in computational theoretical physics
along the two directions outlined above. In the following we shall list
some examples in which a research activity of this type
is already present inside TO61.
- Our research projects can be organized in
two (partially overlapping) main directions (in parenthesis are reported the sections involved,
in their activity reports further information on the research lines can be found):
1] Numerical simulations of systems of biological interest.
In particular:
- protein folding (and misfolding) (FI,MI,PD,PR,RM2,TO)
- molecular dynamics simulations of protein-DNA interactions (MI,TO)
- use of mobility models to describe the cloning expansion in the immune
system.(BO)
- modeling of population dynamics, evolution and coevolution (FI,NA)
- use of agent based models to describe complex biological systems.(BO)
- neural networks (SA,CT)
- dynamic and elastic properties of biomembranes. (NA)
- off equilibrium thermodynamics in nanomanipulation of biomolecules (NA)
- study of peptides complexed with metals using quantum
chemistry methods (RM2)
2] Use of theoretical physics tools (random graph, topology, advanced statistical
mechanics....) to describe general properties of complex systems and in
particular of biological systems.
In particular:
- investigation of physiological signals like EEG, ECG (BA)
- computational approaches to the identification of relevant genomic
structures:
transcription factor binding sites (TO)
RNA secondary structures (CT)
modeling and evolution of the genetic code (NA)
- topological entanglement in long polymer chains (PD)
- theoretical analysis of mechanochemical models (BA)
- use of complex networks theory to analyse dynamical sequences of
microarray data (BO,CT)
- use of graph theory to study biological Networks (CT,BO)
- statistical model of tumor growth (CT)
- use of percolation model to study blood vessels formation (NA)
- time series analysis of biological problems (PD)
- use of statistical mechanics and nonlinear dynamics analysis
to model the neural system.(SA) |
Istituto Nazionale di Fisica Nucleare - Piazza dei Caprettari, 70 - 00186 Roma
tel. +39 066840031 - fax +39 0668307924 - email: presidenza@presid.infn.it
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