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Characterization, analysis, simulation and classification of complex networks

Grant number: 10/19440-2
Support type:Regular Research Grants
Duration: March 01, 2011 - February 28, 2013
Field of knowledge:Physical Sciences and Mathematics - Physics
Principal Investigator:Francisco Aparecido Rodrigues
Grantee:Francisco Aparecido Rodrigues
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The study of complex networks is a relatively new area of science inspired by the empirical studies of real-world networks such as social and biological networks. This area has a highly multidisciplinary nature, which has brought together researchers from many areas including mathematics, physics, biology, computer science, sociology, epidemiology, statistics and others. As a matter of fact, many phenomena in nature can be modeled as a network, such as brain structures, protein-protein interactions, social organizations, financial market relationships, Internet, and World Wide Web. All such systems can be represented in terms of graphs, \emph{i.e.} nodes connected by edges. The organization of these systems has a fundamental influence over different dynamic process. For instance, highly connected routers are fundamental to maintain the performance of the Internet, while people who have a large number of friends present a high rate of disease spreading. At the same time, recent studies have shown that the structure of the brain is related to neural diseases, such as epilepsy. In this project, we present a methodology to study the relationship between the structure of complex networks and different dynamics. Such studies include synchronization, cascade fails, epidemic spreading and transport in networks. The network topology will be characterized by data mining methods, which allow to classify networks according to a set of models and determine patterns of connections in networks. These investigations will be applied to different areas, such as neuroscience, systems biology, economy, meteorology and food webs. (AU)

Articles published in Agência FAPESP Newsletter about the research grant
Study seeks to enhance diagnosis of schizophrenia through imaging 

Scientific publications (13)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
RIBEIRO MELLO, MARCO AURELIO; RODRIGUES, FRANCISCO APARECIDO; COSTA, LUCIANO DA FONTOURA; DANIEL KISSLING, W.; SEKERCIOGLU, CAGAN H.; DARCIE MARQUITTI, FLAVIA MARIA; VIKTORIA KALKO, ELISABETH KLARA. Keystone species in seed dispersal networks are mainly determined by dietary specialization. OIKOS, v. 124, n. 8, p. 1031-1039, AUG 2015. Web of Science Citations: 41.
PERON, THOMAS K. D. M.; JI, PENG; RODRIGUES, FRANCISCO A.; KURTHS, JURGEN. Effects of assortative mixing in the second-order Kuramoto model. Physical Review E, v. 91, n. 5 MAY 11 2015. Web of Science Citations: 17.
DE ARRUDA, GUILHERME FERRAZ; COSTA, LUCIANO DA FONTOURA; SCHUBERT, DIRK; RODRIGUES, FRANCISCO A. Structure and dynamics of functional networks in child-onset schizophrenia. CLINICAL NEUROPHYSIOLOGY, v. 125, n. 8, p. 1589-1595, AUG 2014. Web of Science Citations: 4.
AMANCIO, DIEGO RAPHAEL; COMIN, CESAR HENRIQUE; CASANOVA, DALCIMAR; TRAVIESO, GONZALO; BRUNO, ODEMIR MARTINEZ; RODRIGUES, FRANCISCO APARECIDO; COSTA, LUCIANO DA FONTOURA. A Systematic Comparison of Supervised Classifiers. PLoS One, v. 9, n. 4 APR 24 2014. Web of Science Citations: 67.
PERON, T. K. D.; COMIN, C. H.; AMANCIO, D. R.; COSTA, L. DA F.; RODRIGUES, F. A.; KURTHS, J. Correlations between climate network and relief data. Nonlinear Processes in Geophysics, v. 21, n. 6, p. 1127-1132, 2014. Web of Science Citations: 7.
DE ARRUDA, GUILHERME F.; DAL'MASO PERON, THOMAS KAUE; DE ANDRADE, MARINHO GOMES; ACHCAR, JORGE ALBERTO; RODRIGUES, FRANCISCO APARECIDO. The Influence of Network Properties on the Synchronization of Kuramoto Oscillators Quantified by a Bayesian Regression Analysis. Journal of Statistical Physics, v. 152, n. 3, p. 519-533, AUG 2013. Web of Science Citations: 2.
DAL'MASO PERON, THOMAS KAUE; RODRIGUES, FRANCISCO A.; KURTHS, JUERGEN. Synchronization in clustered random networks. Physical Review E, v. 87, n. 3 MAR 12 2013. Web of Science Citations: 9.
DE GOUVEIA, LILIAN TAIS; DE ARRUDA, GUILHERME FERRAZ; RODRIGUES, FRANCISCO APARECIDO; SENGER, LUCIANO JOSE; COSTA, LUCIANO DA FONTOURA. Supervised Classification of Basaltic Aggregate Particles Based on Texture Properties. JOURNAL OF COMPUTING IN CIVIL ENGINEERING, v. 27, n. 2, p. 177-182, MAR 2013. Web of Science Citations: 1.
DE ARRUDA, GUILHERME F.; COSTA, LUCIANO DA FONTOURA; RODRIGUES, FRANCISCO A. A complex networks approach for data clustering. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v. 391, n. 23, p. 6174-6183, DEC 1 2012. Web of Science Citations: 8.
DAL'MASO PERON, THOMAS KAUE; RODRIGUES, FRANCISCO A. Determination of the critical coupling of explosive synchronization transitions in scale-free networks by mean-field approximations. Physical Review E, v. 86, n. 5, 2 NOV 12 2012. Web of Science Citations: 36.
DAL'MASO PERON, THOMAS KAUE; RODRIGUES, FRANCISCO A. Explosive synchronization enhanced by time-delayed coupling. Physical Review E, v. 86, n. 1, 2 JUL 6 2012. Web of Science Citations: 42.
DAL'MASO PERON, THOMAS KAUE; COSTA, LUCIANO DA FONTOURA; RODRIGUES, FRANCISCO A. The structure and resilience of financial market networks. Chaos, v. 22, n. 1 MAR 2012. Web of Science Citations: 39.
DAL'MASO PERON, T. K.; RODRIGUES, F. A. Collective behavior in financial markets. EPL, v. 96, n. 4 NOV 2011. Web of Science Citations: 29.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.