Statistically Validated Networks in Bipartite Complex Systems

Tumminello, Michele; Miccichè, Salvatore; Lillo, Fabrizio; Piilo, Jyrki; Mantegna, Rosario N.

doi:10.1371/journal.pone.0017994

Cited by 219 publications

(248 citation statements)

References 31 publications

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“…Bipartite networks are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set. A new methodology to statistically validate each link of the projected network against a null hypothesis taking into account the heterogeneity of the system has been recently introduced [6].…”

Section: Statistically Validated Networkmentioning

confidence: 99%

“…a gene-based weighted network in which the nodes are the terms and a link between any two terms is set up whenever a gene is annotated in both terms [5]. Recently a methodology has been proposed that identifies preferential links in the projected network [6], i.e. links whose presence in the projected network cannot be explained in terms of a random co-occurrence of neighbors in the bipartite system.…”

Section: Introductionmentioning

confidence: 99%

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Gene-based and semantic structure of the Gene Ontology as a complex network

Coronnello

Tumminello

Miccichè

2016

Physica A: Statistical Mechanics and its Applications

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a b s t r a c tThe last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The Gene Ontology (GO) is constantly evolving over time. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. Here we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium. Moreover, the GO is a natural example of bipartite network of terms and genes. Here we are interested in studying the properties of the projected network of terms, i.e. a gene-based weighted network of GO terms, in which a link between any two terms is set if at least one gene is annotated in both terms. One aim of the present paper is to compare the structural properties of the semantic and the gene-based network. The relative importance of terms is very similar in the two networks, but the community structure changes. We show that in some cases GO terms that appear to be distinct from a semantic point of view are instead connected, and appear in the same community when considering their gene content. The identification of such gene-based communities of terms might therefore be the basis of a simple protocol aiming at improving the semantic structure of GO. Information about terms that share large gene content might also be important from a biomedical point of view, as it might reveal how genes over-expressed in a certain term also affect other biological processes, molecular functions and cellular components not directly linked according to GO semantics.

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Section: Statistically Validated Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Gene-based and semantic structure of the Gene Ontology as a complex network

Coronnello

Tumminello

Miccichè

2016

Physica A: Statistical Mechanics and its Applications

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“…Our test is done by using a recently proposed method (40,41) that is a directional variant of the method presented in Ref. (42,43). The statistical test is implemented as follows.…”

Section: A Null Hypothesis For the Number Of Loans Between Two Banksmentioning

confidence: 99%

Quantifying preferential trading in the e-MID interbank market

Hatzopoulos

Iori

Mantegna

et al. 2014

Quantitative Finance

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Interbank markets allow credit institutions to exchange capital for purposes of liquidity management. These markets are among the most liquid markets in the financial system. However, liquidity of interbank markets dropped during the 2007-2008 financial crisis, and such a lack of liquidity influenced the entire economic system. In this paper, we analyze transaction data from the e-MID market which is the only electronic interbank market in the Euro Area and US, over a period of eleven years (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)). We adapt a method developed to detect statistically validated links in a network, in order to reveal preferential trading in a directed network. Preferential trading between banks is detected by comparing empirically observed trading relationships with a null hypothesis that assumes random trading among banks doing a heterogeneous number of transactions. Preferential trading patterns are revealed at time windows of 3-maintenance periods. We show that preferential trading is observed throughout the whole period of analysis and that the number of preferential trading links does not show any significant trend in time, in spite of a decreasing trend in the number of pairs of banks making transactions. We observe that preferential trading connections typically involve large trading volumes. During the crisis, we also observe that transactions occurring between banks with a preferential connection occur at larger interest rates than the complement set -an effect that is not observed before the crisis. Permanent repository link

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“…actors), such that every link connects a node in ⊤ to one in ⊥. Bipartite graphs are a fundamental object which has proven to be very efficient for both the analysis [5,16,1,14] and the modelling [3,15] of complex networks as it is able to reveal patterns that could not have been detected on simple graphs.…”

Section: Introductionmentioning

confidence: 99%

Comparing Overlapping Properties of Real Bipartite Networks

Tarissan

2015

ISCS 2014: Interdisciplinary Symposium on Complex Systems

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Abstract. Many real-world networks lend themselves to the use of graphs for analysing and modelling their structure. But such a simple representation has proven to miss some important and non trivial properties hidden in the bipartite structure of the networks. Recent papers have shown that overlapping properties seem to be present in bipartite networks and that it could explain better the properties observed in simple graphs. This work intends to investigate this question by studying two proposed metrics to account for overlapping structures in bipartite networks. The study, conducted on four dataset stemming from very different contexts (computer science, juridical science and social science), shows that the most popular metrics, the clustering coefficient, turns out to be less relevant that the recent redundancy coefficient to analyse intricate overlapping properties of real networks.

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Statistically Validated Networks in Bipartite Complex Systems

Cited by 219 publications

References 31 publications

Gene-based and semantic structure of the Gene Ontology as a complex network

Gene-based and semantic structure of the Gene Ontology as a complex network

Quantifying preferential trading in the e-MID interbank market

Comparing Overlapping Properties of Real Bipartite Networks

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