Upcoming Seminars - Tuesday 16 June

[Quantitative Life Sciences]

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UPCOMING SEMINARS - QLS & Spring College on the Physics of Complex Systems
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Special NETADIS Session on Statistical Mechanics of Inference



TUESDAY, 16 JUNE
GIAMBIAGI Lecture Hall - ICTP Adriatico Guest House


14:30 Barbara Bravi (King's College London, UK)

Title: Extended Plefka Expansion for Stochastic Dynamics

Abstract:
We propose an extension of the Plefka expansion, which is well known for 
the dynamics of discrete spins, to stochastic differential equations 
with continuous degrees of freedom and exhibiting generic 
nonlinearities. The scenario is sufficiently general to allow 
application to e.g. biochemical networks involved in metabolism and 
regulation. The main feature of our approach is to constrain in the 
Plefka expansion not just first moments akin to magnetizations, but also 
second moments, specifically two-time correlations and responses for 
each degree of freedom. The end result is an effective equation of 
motion for each single degree of freedom, where couplings to other 
variables appear as a self-coupling to the past (i.e. memory term) and a 
coloured noise. This constitutes a new mean field approximation that 
should become exact in the thermodynamic limit of a large network, for 
suitably long-ranged couplings. For the analytically tractable case of 
linear dynamics we establish this exactness explicitly by appeal to 
spectral methods of Random Matrix Theory, for Gaussian couplings with 
arbitrary degree of symmetry.

Authors: B Bravi, P Sollich, M Opper

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15:10 Caterina De Bacco (LPTMS, Centre National de la Recherche 
Scientifique et Université Paris-Sud 11, Orsay, France)

Title: The cavity method in routing optimization problems on networks

Abstract:
In recent years the cavity method, or message-passing algorithm, has 
been successfully exploited by statistical physicists to solve 
combinatorial optimization problems such as the K-satisfability (K-SAT). 
In this talk we introduce this method and outline how it is applied to 
solve routing problems on communication or traffic networks. In this 
context the typical situation is where many users want to communicate at 
the same time over a given network. One then wants to optimize the 
overall routing by minimizing communication path length and the traffic 
overlap either at nodes or at edges given a set of constraints. We will 
show how the cavity method provides the algorithmic tools to tackle 
these types of optimization problems efficiently

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15:50 Silvia Grigolon (LPTMS, Univ. Paris - Sud, Orsay, France)

Title: Identifying relevant positions in proteins by Critical Variable 
Selection

Abstract:
In the last decades development of better inference methods on data 
samples has been one of the central points of interest for the wide 
research community focused on complex systems.
Normally, the main idea is that of assuming a model to be the best one 
describing a system and exploiting correlation functions – defined in 
the most suitable way for a given dataset – to find out a sort of 
hierarchy in the interaction network arising out of a given data sample. 
The aim is then that of finding out whether there are and who are the 
key–players and finally what kind of interactions are set among them.
Here we present a natural application of a new method [M. Marsili et 
al., J. Stat. Mech., P09003, 2013], renamed Critical Variable Selection, 
which does not take directly into account two-points correlations but is 
able to select the best ways for a set of variables to cluster, in the 
particular case maximizing an information amount defined on the 
clustering itself. In protein sequences, this leads for instance to the 
selection of a subset of sites turning out to be key–points not only 
along the primary but also along the tertiary structure of the protein 
itself.
The results obtained by the study of two protein families, Che-Y 
receptors and the ion channels, compared with those turning out from the 
application of Statistical Coupling Analysis, being a generalization of 
the Principal Component Analysis [V. Plerou et al., Phys. Rev. Lett., 
83:7, 1471-74, 1999, N. Halabi et al., Cell, 138:4, 774-86, 2009] show 
interesting overlaps between the two methods, being the new one also 
able to identify most of the tightest contacts in the proteins tertiary 
structures [F. Morcos et al., PNAS, 108:49, E12093-301, 2011].


-- 
Erica Sarnataro
Group Secretary
Quantitative Life Sciences
The Abdus Salam International Centre for Theoretical Physics (ICTP)
Trieste,  Italy
Tel. +39-040-2240623
e-mail: qls at ictp.it