4,864 research outputs found
Analyzing and Visualizing American Congress Polarization and Balance with Signed Networks
Signed networks and balance theory provide a natural setting for real-world
scenarios that show polarization dynamics, positive/negative relationships, and
political partisanships. For example, they have been proven effective for
studying the increasing polarization of the votes in the two chambers of the
American Congress from World War II on.
To provide further insights into this particular case study, we propose the
application of a framework to analyze and visualize a signed graph's
configuration based on the exploitation of the corresponding Laplacian matrix'
spectral properties. The overall methodology is comparable with others based on
the frustration index, but it has at least two main advantages: first, it
requires a much lower computational cost; second, it allows for a quantitative
and visual assessment of how arbitrarily small subgraphs (even single nodes)
contribute to the overall balance (or unbalance) of the network.
The proposed pipeline allows to explore the polarization dynamics shown by
the American Congress from 1945 to 2020 at different resolution scales. In
fact, we are able to spot and to point out the influence of some (groups of)
congressmen in the overall balance, as well as to observe and explore
polarization's evolution of both chambers across the years
Polarization and multiscale structural balance in signed networks
Polarization is a common feature of social systems. Structural Balance Theory
studies polarization of positive in-group and negative out-group ties in terms
of semicycles within signed networks. However, enumerating semicycles is
computationally expensive, so approximations are often needed to assess
balance. Here we introduce Multiscale Semiwalk Balance (MSB) approach for
quantifying the degree of balance (DoB) in (un)directed, (un)weighted signed
networks by approximating semicycles with closed semiwalks. MSB allows
principled selection of a range of cycle lengths appropriate for assessing DoB
and interpretable under the Locality Principle (which posits that patterns in
shorter cycles are crucial for balance). This flexibility overcomes several
limitations affecting walk-based approximations and enables efficient,
interpretable methods for measuring DoB and clustering signed networks. We
demonstrate the effectiveness of our approach by applying it to real-world
social systems. For instance, our methods capture increasing polarization in
the U.S. Congress, which may go undetected with other methods.Comment: 29 pages; 7 figures; preprint before peer revie
Monotonicity, frustration, and ordered response: an analysis of the energy landscape of perturbed large-scale biological networks
<p>Abstract</p> <p>Background</p> <p>For large-scale biological networks represented as signed graphs, the index of frustration measures how far a network is from a monotone system, i.e., how incoherently the system responds to perturbations.</p> <p>Results</p> <p>In this paper we find that the frustration is systematically lower in transcriptional networks (modeled at functional level) than in signaling and metabolic networks (modeled at stoichiometric level). A possible interpretation of this result is in terms of energetic cost of an interaction: an erroneous or contradictory transcriptional action costs much more than a signaling/metabolic error, and therefore must be avoided as much as possible. Averaging over all possible perturbations, however, we also find that unlike for transcriptional networks, in the signaling/metabolic networks the probability of finding the system in its least frustrated configuration tends to be high also in correspondence of a moderate energetic regime, meaning that, in spite of the higher frustration, these networks can achieve a globally ordered response to perturbations even for moderate values of the strength of the interactions. Furthermore, an analysis of the energy landscape shows that signaling and metabolic networks lack energetic barriers around their global optima, a property also favouring global order.</p> <p>Conclusion</p> <p>In conclusion, transcriptional and signaling/metabolic networks appear to have systematic differences in both the index of frustration and the transition to global order. These differences are interpretable in terms of the different functions of the various classes of networks.</p
Computational approaches to complex biological networks
The need of understanding and modeling the biological networks is one of the raisons d'\ueatre and of the driving forces behind the emergence of Systems Biology. Because of its holistic approach and because of the widely different level of complexity of the networks, different mathematical methods have been developed during the years. Some of these computational methods are used in this thesis in order to investigate various properties of different biological systems. The first part deals with the prediction of the perturbation of cellular metabolism induced by drugs. Using Flux Balance Analysis to describe the reconstructed genome-wide metabolic networks, we consider the problem of identifying the most selective drug synergisms for given therapeutic targets. The second part of this thesis considers gene regulatory and large social networks as signed graphs (activation/deactivation or friendship/hostility are rephrased as positive/negative coupling between spins). Using the analogy with an Ising spin glass an analysis of the energy landscape and of the content of \u201cdisorder\u201d 'is carried out. Finally, the last part concerns the study of the spatial heterogeneity of the signaling pathway of rod photoreceptors. The electrophysiological data produced by our collaborators in the Neurobiology laboratory have been analyzed with various dynamical systems giving an insight into the process of ageing of photoreceptors and into the role diffusion in the pathway
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