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Abstract: The World Trade Web (WTW), the network defined by the international import/export trade relationships, has been recently shown to display some important topological properties which are tightly related to the Gross Domestic Product of world countries. While our previous analysis focused on the static, undirected version of the WTW, here we address its full evolving, directed description. This is accomplished by exploiting the peculiar reciprocity structure of the WTW to recover the directed nature of international trade channels, and by studying the temporal dependence of the parameters describing the WTW topology. [Copyright &y& Elsevier]

Abstract: We propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings. In this framework, the in-degree () and the sum of incoming link weights (v) of an investor correspond to the number of assets held (portfolio diversification) and to the invested wealth (portfolio volume), respectively. An empirical analysis of three different real markets reveals that the distributions of both and v display power-law tails with exponents and . Moreover, we find that scales as a power-law function of v with an exponent . Remarkably, despite the values of , and differ across the three markets, they are always governed by the scaling relation . We show that these empirical findings can be reproduced by a recent model relating the emergence of scale-free networks to an underlying Paretian distribution of ‘hidden’ vertex properties. [Copyright &y& Elsevier]

We study a model of wealth dynamics (Physica A 282 (2000) 536) which mimics transactions among economic agents. The outcomes of the model are shown to depend strongly on the topological properties of the underlying transaction network. The extreme cases of a fully connected and a fully disconnected network yield power-law and log-normal forms of the wealth distribution, respectively. We perform numerical simulations in order to test the model on more complex network topologies. We show that the mixed form of most empirical distributions (displaying a non-smooth transition from a log-normal to a power-law form) can be traced back to a heterogeneous topology with varying link density, which on the other hand is a recently observed property of real networks. [Copyright &y& Elsevier]

Abstract The study of social, economic and biological systems is often (when not always) limited by the partial information about the structure of the underlying networks. An example of paramount importance is provided by financial systems: information on the interconnections between financial institutions is privacy-protected, dramatically reducing the possibility of correctly estimating crucial systemic properties such as the resilience to the propagation of shocks. The need to compensate for the scarcity of data, while optimally employing the available information, has led to the birth of a research field known as network reconstruction. Since the latter has benefited from the contribution of researchers working in disciplines as different as mathematics, physics and economics, the results achieved so far are still scattered across heterogeneous publications. Most importantly, a systematic comparison of the network reconstruction methods proposed up to now is currently missing. This review aims at providing a unifying framework to present all these studies, mainly focusing on their application to economic and financial networks. [ABSTRACT FROM AUTHOR]

Abstract: Defining the amino acid composition of protein cores is fundamental for understanding protein folding, as different architectures might achieve structural stability only in the presence of specific amino acid networks. Quantitative characterization of protein cores in relation to the corresponding structures and dynamics is needed to increase the reliability of protein engineering procedures. Unambiguous criteria based on atom depth considerations were established to assign amino acid residues to protein cores and, hence, for classifying inner and outer molecular moieties. These criteria were summarized in a new tool named ProCoCoA, Protein Core Composition Analyzer. An user-friendly web interface was developed, available at the URL: http://www.sbl.unisi.it/prococoa. An accurate estimate of protein core composition for six protein architectures selected from the CATH database of solved structures has been carried out, and the obtained results indicate the presence of specific patterns of amino acid core composition in different protein folds. [Copyright &y& Elsevier]